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  • 301.
    Karayiannidis, Yiannis
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Smith, Christian
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Vina, Francisco
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Kragic, Danica
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Online Contact Point Estimation for Uncalibrated Tool Use2014Ingår i: Robotics and Automation (ICRA), 2014 IEEE International Conference on, IEEE Robotics and Automation Society, 2014, 2488-2493 s.Konferensbidrag (Refereegranskat)
    Abstract [en]

    One of the big challenges for robots working outside of traditional industrial settings is the ability to robustly and flexibly grasp and manipulate tools for various tasks. When a tool is interacting with another object during task execution, several problems arise: a tool can be partially or completely occluded from the robot's view, it can slip or shift in the robot's hand - thus, the robot may lose the information about the exact position of the tool in the hand. Thus, there is a need for online calibration and/or recalibration of the tool. In this paper, we present a model-free online tool-tip calibration method that uses force/torque measurements and an adaptive estimation scheme to estimate the point of contact between a tool and the environment. An adaptive force control component guarantees that interaction forces are limited even before the contact point estimate has converged. We also show how to simultaneously estimate the location and normal direction of the surface being touched by the tool-tip as the contact point is estimated. The stability of the the overall scheme and the convergence of the estimated parameters are theoretically proven and the performance is evaluated in experiments on a real robot.

  • 302.
    Karayiannidis, Yiannis
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Smith, Christian
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Vina, Francisco
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Kragic, Danica
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Online Kinematics Estimation for Active Human-Robot Manipulation of Jointly Held Objects2013Ingår i: 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), IEEE , 2013, 4872-4878 s.Konferensbidrag (Refereegranskat)
    Abstract [en]

    This paper introduces a method for estimating the constraints imposed by a human agent on a jointly manipulated object. These estimates can be used to infer knowledge of where the human is grasping an object, enabling the robot to plan trajectories for manipulating the object while subject to the constraints. We describe the method in detail, motivate its validity theoretically, and demonstrate its use in co-manipulation tasks with a real robot.

  • 303.
    Karayiannidis, Yiannis
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Smith, Christian
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Vina, Francisco
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Ögren, Petter
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Kragic, Danica
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Design of force-driven online motion plans for door opening under uncertainties2012Ingår i: Workshop on Real-time Motion Planning: Online, Reactive, and in Real-time, 2012Konferensbidrag (Refereegranskat)
    Abstract [en]

    The problem of door opening is fundamental for household robotic applications. Domestic environments are generally less structured than industrial environments and thus several types of uncertainties associated with the dynamics and kinematics of a door must be dealt with to achieve successful opening. This paper proposes a method that can open doors without prior knowledge of the door kinematics. The proposed method can be implemented on a velocity-controlled manipulator with force sensing capabilities at the end-effector. The velocity reference is designed by using feedback of force measurements while constraint and motion directions are updated online based on adaptive estimates of the position of the door hinge. The online estimator is appropriately designed in order to identify the unknown directions. The proposed scheme has theoretically guaranteed performance which is further demonstrated in experiments on a real robot. Experimental results additionally show the robustness of the proposed method under disturbances introduced by the motion of the mobile platform.

  • 304.
    Karayiannidis, Yiannis
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Smith, Christian
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Vina, Francisco
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Ögren, Petter
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Kragic, Danica
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Interactive perception and manipulation of unknown constrained mechanisms using adaptive control2013Ingår i: ICRA 2013 Mobile Manipulation Workshop on Interactive Perception, 2013Konferensbidrag (Refereegranskat)
  • 305.
    Karayiannidis, Yiannis
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Smith, Christian
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Vina, Francisco
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Ögren, Petter
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Kragic, Danica
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Model-free robot manipulation of doors and drawers by means of fixed-grasps2013Ingår i: 2013 IEEE International Conference on Robotics and Automation (ICRA), New York: IEEE , 2013, 4485-4492 s.Konferensbidrag (Refereegranskat)
    Abstract [en]

    This paper addresses the problem of robot interaction with objects attached to the environment through joints such as doors or drawers. We propose a methodology that requires no prior knowledge of the objects’ kinematics, including the type of joint - either prismatic or revolute. The method consists of a velocity controller which relies onforce/torque measurements and estimation of the motion direction,rotational axis and the distance from the center of rotation.The method is suitable for any velocity controlled manipulatorwith a force/torque sensor at the end-effector. The force/torquecontrol regulates the applied forces and torques within givenconstraints, while the velocity controller ensures that the endeffectormoves with a task-related desired tangential velocity. The paper also provides a proof that the estimates converge tothe actual values. The method is evaluated in different scenarios typically met in a household environment.

  • 306.
    Karayiannidis, Yiannis
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Smith, Christian
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Vina, Francisco
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Ögren, Petter
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Kragic, Danica
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    "Open Sesame!" Adaptive Force/Velocity Control for Opening Unknown Doors2012Ingår i: Intelligent Robots and Systems (IROS), 2012 IEEE/RSJ International Conference on, IEEE , 2012, 4040-4047 s.Konferensbidrag (Refereegranskat)
    Abstract [en]

    The problem of door opening is fundamental for robots operating in domestic environments. Since these environments are generally less structured than industrial environments, several types of uncertainties associated with the dynamics and kinematics of a door must be dealt with to achieve successful opening. This paper proposes a method that can open doors without prior knowledge of the door kinematics. The proposed method can be implemented on a velocity-controlled manipulator with force sensing capabilities at the end-effector. The method consists of a velocity controller which uses force measurements and estimates of the radial direction based on adaptive estimates of the position of the door hinge. The control action is decomposed into an estimated radial and tangential direction following the concept of hybrid force/motion control. A force controller acting within the velocity controller regulates the radial force to a desired small value while the velocity controller ensures that the end effector of the robot moves with a desired tangential velocity leading to task completion. This paper also provides a proof that the adaptive estimates of the radial direction converge to the actual radial vector. The performance of the control scheme is demonstrated in both simulation and on a real robot.

  • 307.
    Karayiannidis, Yiannis
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Smith, Christian
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Ögren, Petter
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Kragic, Danica
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Adaptive force/velocity control for opening unknown doors2012Ingår i: Robot Control, Volume 10, Part  1, 2012, 753-758 s.Konferensbidrag (Refereegranskat)
    Abstract [en]

    The problem of door opening is fundamental for robots operating in domesticenvironments. Since these environments are generally unstructured, a robot must deal withseveral types of uncertainties associated with the dynamics and kinematics of a door to achievesuccessful opening. The present paper proposes a dynamic force/velocity controller which usesadaptive estimation of the radial direction based on adaptive estimates of the door hinge’sposition. The control action is decomposed into estimated radial and tangential directions,which are proved to converge to the corresponding actual values. The force controller usesreactive compensation of the tangential forces and regulates the radial force to a desired smallvalue, while the velocity controller ensures that the robot’s end-effector moves with a desiredtangential velocity. The performance of the control scheme is demonstrated in simulation witha 2 DoF planar manipulator opening a door.

  • 308.
    Karipidou, Kelly
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Modelling the body language of a musical conductor using Gaussian Process Latent Variable Models2015Självständigt arbete på avancerad nivå (masterexamen), 20 poäng / 30 hpStudentuppsats (Examensarbete)
    Abstract [en]

    Motion capture data of a musical conductor's movements when conducting a string quartet is analysed in this work using the Gaussian Process Latent Variable Model (GP-LVM) framework. A dimensionality reduction on the high dimensional motion capture data to a two dimensional representation using a GP-LVM is performed, followed by classification of conduction movements belonging to different interpretations of the same musical piece. A dynamical prior is used for the GP-LVM, resulting in a representative latent space for the sequential conduction motion data. Classification results with great performance for some of the interpretations are obtained. The GP-LVM with dynamical prior distribution is shown to be a reasonable choice when wanting to model conduction data, opening up the possibility for creating for example a "conduct-your-own-orchestra" system in a principled mathematical way, in the future.

  • 309.
    Karlsson, Jesper
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Enhancing Object RecognitionBased on Contextual InformationUsing Markov Logic Networks2016Självständigt arbete på avancerad nivå (masterexamen), 80 poäng / 120 hpStudentuppsats (Examensarbete)
    Abstract [en]

    Perception is a crucial part of an autonomous robotic system, as it processes sensory input and extracts useful information for action planning and execution such as recognizing objects in the environment where the robot is to act. Although object recognition has been studied extensively and a lot of progress has been made, current systems often face difficulties in dealing with ambiguities and uncertainties in the raw sensory data. It has been shown that using contextual information can reduce these ambiguities, however many different types of context measures exist and it is not always clear which type is the most effective for classification purposes.In this thesis we study how and to what extentMarkov Logic Networks (MLN) can be used to increase robustness in object classification by making use of context. MLNs consist of a combination of first-order logic and Markov Random fields, allowing for a solid framework for defining soft and hard rules that can be used efficiently in classification. Structure learning methods for MLNs allow for automatic improvement of the structure as well as flexibility when expanding the classification space. Therefore, it was of particular interest to study how the learning of the structure of an MLN performed against a manually constructed counterpart. We propose spatial relations, e.g.,’isRightTo’, ’isLeftTo’ and ’isAbove’, as a measure of context in order to reduce classification errors of items in various household scenes. Our experimental evaluations start with a comparison with a commonly used probabilistic classifier, the NaiveBayes classifier. Furthermore, we use a publicly available dataset to compare structure learning with a state-of-the-art system which uses MLNs with a manually designed structure. In addition, we test our approach with and without spatial relations on this dataset. Overall, the results show that MLNs outperform conventional classification algorithms and that spatial relations and structure learning increase the classification accuracy.

  • 310.
    Kazemi, Vahid
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Correspondence Estimation in Human Face and Posture Images2014Doktorsavhandling, sammanläggning (Övrigt vetenskapligt)
    Abstract [en]

    Many computer vision tasks such as object detection, pose estimation,and alignment are directly related to the estimation of correspondences overinstances of an object class. Other tasks such as image classification andverification if not completely solved can largely benefit from correspondenceestimation. This thesis presents practical approaches for tackling the corre-spondence estimation problem with an emphasis on deformable objects.Different methods presented in this thesis greatly vary in details but theyall use a combination of generative and discriminative modeling to estimatethe correspondences from input images in an efficient manner. While themethods described in this work are generic and can be applied to any object,two classes of objects of high importance namely human body and faces arethe subjects of our experimentations.When dealing with human body, we are mostly interested in estimating asparse set of landmarks – specifically we are interested in locating the bodyjoints. We use pictorial structures to model the articulation of the body partsgeneratively and learn efficient discriminative models to localize the parts inthe image. This is a common approach explored by many previous works. Wefurther extend this hybrid approach by introducing higher order terms to dealwith the double-counting problem and provide an algorithm for solving theresulting non-convex problem efficiently. In another work we explore the areaof multi-view pose estimation where we have multiple calibrated cameras andwe are interested in determining the pose of a person in 3D by aggregating2D information. This is done efficiently by discretizing the 3D search spaceand use the 3D pictorial structures model to perform the inference.In contrast to the human body, faces have a much more rigid structureand it is relatively easy to detect the major parts of the face such as eyes,nose and mouth, but performing dense correspondence estimation on facesunder various poses and lighting conditions is still challenging. In a first workwe deal with this variation by partitioning the face into multiple parts andlearning separate regressors for each part. In another work we take a fullydiscriminative approach and learn a global regressor from image to landmarksbut to deal with insufficiency of training data we augment it by a large numberof synthetic images. While we have shown great performance on the standardface datasets for performing correspondence estimation, in many scenariosthe RGB signal gets distorted as a result of poor lighting conditions andbecomes almost unusable. This problem is addressed in another work wherewe explore use of depth signal for dense correspondence estimation. Hereagain a hybrid generative/discriminative approach is used to perform accuratecorrespondence estimation in real-time.

  • 311.
    Kazemi, Vahid
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Burenius, Magnus
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Azizpour, Hossein
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Sullivan, Josephine
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Multi-view body part recognition with random forests2013Ingår i: BMVC 2013 - Electronic Proceedings of the British Machine Vision Conference 2013, Bristol, England: British Machine Vision Association , 2013Konferensbidrag (Refereegranskat)
    Abstract [en]

    This paper addresses the problem of human pose estimation, given images taken from multiple dynamic but calibrated cameras. We consider solving this task using a part-based model and focus on the part appearance component of such a model. We use a random forest classifier to capture the variation in appearance of body parts in 2D images. The result of these 2D part detectors are then aggregated across views to produce consistent 3D hypotheses for parts. We solve correspondences across views for mirror symmetric parts by introducing a latent variable. We evaluate our part detectors qualitatively and quantitatively on a dataset gathered from a professional football game.

  • 312.
    Kazemi, Vahid
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Josephine, Sullivan
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    One Millisecond Face Alignment with an Ensemble of Regression Trees2014Ingår i: 2014 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), IEEE Computer Society, 2014, 1867-1874 s.Konferensbidrag (Refereegranskat)
    Abstract [en]

    This paper addresses the problem of Face Alignment for a single image. We show how an ensemble of regression trees can be used to estimate the face's landmark positions directly from a sparse subset of pixel intensities, achieving super-realtime performance with high quality predictions. We present a general framework based on gradient boosting for learning an ensemble of regression trees that optimizes the sum of square error loss and naturally handles missing or partially labelled data. We show how using appropriate priors exploiting the structure of image data helps with efficient feature selection. Different regularization strategies and its importance to combat overfitting are also investigated. In addition, we analyse the effect of the quantity of training data on the accuracy of the predictions and explore the effect of data augmentation using synthesized data.

  • 313.
    Kazemi, Vahid
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. Microsoft Research, United States.
    Keskin, Cem
    Microsoft Research, United States.
    Taylor, Jonathan
    Microsoft Research, United States.
    Kholi, Pushmeet
    Microsoft Research, United States.
    Izadi, Shahram
    Microsoft Research, United States.
    Real-time Face Reconstruction from a Single Depth Image2014Ingår i: Proceedings - 2014 International Conference on 3D Vision, 3DV 2014, IEEE conference proceedings, 2014, 369-376 s.Konferensbidrag (Refereegranskat)
    Abstract [en]

    This paper contributes a real time method for recovering facial shape and expression from a single depth image. The method also estimates an accurate and dense correspondence field between the input depth image and a generic face model. Both outputs are a result of minimizing the error in reconstructing the depth image, achieved by applying a set of identity and expression blend shapes to the model. Traditionally, such a generative approach has shown to be computationally expensive and non-robust because of the non-linear nature of the reconstruction error. To overcome this problem, we use a discriminatively trained prediction pipeline that employs random forests to generate an initial dense but noisy correspondence field. Our method then exploits a fast ICP-like approximation to update these correspondences, allowing us to quickly obtain a robust initial fit of our model. The model parameters are then fine tuned to minimize the true reconstruction error using a stochastic optimization technique. The correspondence field resulting from our hybrid generative-discriminative pipeline is accurate and useful for a variety of applications such as mesh deformation and retexturing. Our method works in real-time on a single depth image i.e. without temporal tracking, is free from per-user calibration, and works in low-light conditions.

  • 314.
    Kazemi, Vahid
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Sullivan, Josephine
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Face Alignment with Part-Based Modeling2011Ingår i: BMVC 2011 - Proceedings of the British Machine Vision Conference 2011 / [ed] Hoey, Jesse and McKenna, Stephen and Trucco, Emanuele, UK: British Machine Vision Association, BMVA , 2011, 27.1-27.10 s.Konferensbidrag (Refereegranskat)
    Abstract [en]

    We propose a new method for face alignment with part-based modeling. This method is competitive in terms of precision with existing methods such as Active Appearance Models, but is more robust and has a superior generalization ability due to its part-based nature. A variation of the Histogram of Oriented Gradients descriptor is used to model the appearance of each part and the shape information is represented with a set of landmark points around the major facial features. Multiple linear regression models are learnt to estimate the position of the landmarks from the appearance of each part. We verify our algorithm with a set of experiments on human faces and these show the competitive performance of our method compared to existing methods.

  • 315.
    Kazemi, Vahid
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Sullivan, Josephine
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Using Richer Models for Articulated Pose Estimation of Footballers2012Ingår i: Proceedings British Machine Vision Conference 2012., 2012, 6.1-6.10 s.Konferensbidrag (Refereegranskat)
    Abstract [en]

    We present a fully automatic procedure for reconstructing the pose of a person in 3Dfrom images taken from multiple views. We demonstrate a novel approach for learningmore complex models using SVM-Rank, to reorder a set of high scoring configurations.The new model in many cases can resolve the problem of double counting of limbswhich happens often in the pictorial structure based models. We address the problemof flipping ambiguity to find the correct correspondences of 2D predictions across allviews. We obtain improvements for 2D prediction over the state of art methods on ourdataset. We show that the results in many cases are good enough for a fully automatic3D reconstruction with uncalibrated cameras.

  • 316.
    Kjellström, Hedvig
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Contextual Action Recognition2011Ingår i: Visual Analysis of Humans : Looking at People / [ed] T. B. Moeslund, A. Hilton, V. Krüger and L. Sigal, Springer , 2011, 355-376 s.Kapitel i bok, del av antologi (Övrigt vetenskapligt)
  • 317.
    Kjellström, Hedvig
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Engwall, Olov
    KTH, Skolan för datavetenskap och kommunikation (CSC), Tal, musik och hörsel, TMH, Tal-kommunikation.
    Audiovisual-to-articulatory inversion2009Ingår i: Speech Communication, ISSN 0167-6393, E-ISSN 1872-7182, Vol. 51, nr 3, 195-209 s.Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    It has been shown that acoustic-to-articulatory inversion, i.e. estimation of the articulatory configuration from the corresponding acoustic signal, can be greatly improved by adding visual features extracted from the speaker's face. In order to make the inversion method usable in a realistic application, these features should be possible to obtain from a monocular frontal face video, where the speaker is not required to wear any special markers. In this study, we investigate the importance of visual cues for inversion. Experiments with motion capture data of the face show that important articulatory information can be extracted using only a few face measures that mimic the information that could be gained from a video-based method. We also show that the depth cue for these measures is not critical, which means that the relevant information can be extracted from a frontal video. A real video-based face feature extraction method is further presented, leading to similar improvements in inversion quality. Rather than tracking points on the face, it represents the appearance of the mouth area using independent component images. These findings are important for applications that need a simple audiovisual-to-articulatory inversion technique, e.g. articulatory phonetics training for second language learners or hearing-impaired persons.

  • 318.
    Kjellström, Hedvig
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Engwall, Olov
    KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Talteknologi, CTT. KTH, Skolan för datavetenskap och kommunikation (CSC), Tal, musik och hörsel, TMH, Tal-kommunikation.
    Abdou, Sherif
    Bälter, Olle
    KTH, Skolan för datavetenskap och kommunikation (CSC), Människa-datorinteraktion, MDI.
    Audio-visual phoneme classification for pronunciation training applications2007Ingår i: INTERSPEECH 2007: 8TH ANNUAL CONFERENCE OF THE INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION, BAIXAS: ISCA-INST SPEECH COMMUNICATION ASSOC , 2007, 57-60 s.Konferensbidrag (Refereegranskat)
    Abstract [en]

    We present a method for audio-visual classification of Swedish phonemes, to be used in computer-assisted pronunciation training. The probabilistic kernel-based method is applied to the audio signal and/or either a principal or an independent component (PCA or ICA) representation of the mouth region in video images. We investigate which representation (PCA or ICA) that may be most suitable and the number of components required in the base, in order to be able to automatically detect pronunciation errors in Swedish from audio-visual input. Experiments performed on one speaker show that the visual information help avoiding classification errors that would lead to gravely erroneous feedback to the user; that it is better to perform phoneme classification on audio and video separately and then fuse the results, rather than combining them before classification; and that PCA outperforms ICA for fewer than 50 components.

  • 319.
    Kjellström, Hedvig
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Kragic, Danica
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Black, Michael J.
    Tracking People Interacting with Objects2010Ingår i: 2010 IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR), 2010, 747-754 s.Konferensbidrag (Refereegranskat)
    Abstract [en]

    While the problem of tracking 3D human motion has been widely studied, most approaches have assumed that the person is isolated and not interacting with the environment. Environmental constraints, however, can greatly constrain and simplify the tracking problem. The most studied constraints involve gravity and contact with the ground plane. We go further to consider interaction with objects in the environment. In many cases, tracking rigid environmental objects is simpler than tracking high-dimensional human motion. When a human is in contact with objects in the world, their poses constrain the pose of body, essentially removing degrees of freedom. Thus what would appear to be a harder problem, combining object and human tracking, is actually simpler. We use a standard formulation of the body tracking problem but add an explicit model of contact with objects. We find that constraints from the world make it possible to track complex articulated human motion in 3D from a monocular camera.

  • 320.
    Kjellström, Hedvig
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Romero, Javier
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Kragic, Danica
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Visual Recognition of Grasps for Human-to-Robot Mapping2008Ingår i: 2008 IEEE/RSJ International Conference On Robots And Intelligent Systems, Vols 1-3, Conference Proceedings / [ed] Chatila, R; Kelly, A; Merlet, JP, 2008, 3192-3199 s.Konferensbidrag (Refereegranskat)
    Abstract [en]

    This paper presents a vision based method for grasp classification. It is developed as part of a Programming by Demonstration (PbD) system for which recognition of objects and pick-and-place actions represent basic building blocks for task learning. In contrary to earlier approaches, no articulated 3D reconstruction of the hand over time is taking place. The indata consists of a single image of the human hand. A 2D representation of the hand shape, based on gradient orientation histograms, is extracted from the image. The hand shape is then classified as one of six grasps by finding similar hand shapes in a large database of grasp images. The database search is performed using Locality Sensitive Hashing (LSH), an approximate k-nearest neighbor approach. The nearest neighbors also give an estimated hand orientation with respect to the camera. The six human grasps are mapped to three Barret hand grasps. Depending on the type of robot grasp, a precomputed grasp strategy is selected. The strategy is further parameterized by the orientation of the hand relative to the object. To evaluate the potential for the method to be part of a robust vision system, experiments were performed, comparing classification results to a baseline of human classification performance. The experiments showed the LSH recognition performance to be comparable to human performance.

  • 321.
    Kjellström, Hedvig
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Romero, Javier
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Martinez, David
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Kragic, Danica
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Simultaneous Visual Recognition of Manipulation Actions and Manipulated Objects2008Ingår i: Computer Vision - Eccv 2008, Pt Ii, Proceedings / [ed] Forsyth, D; Torr, P; Zisserman, A, 2008, Vol. 5303, 336-349 s.Konferensbidrag (Refereegranskat)
    Abstract [en]

    The visual analysis of human manipulation actions is of interest for e.g. human-robot interaction applications where a robot learns how to perform a task by watching a human. In this paper, a method for classifying manipulation actions in the context of the objects manipulated, and classifying objects in the context of the actions used to manipulate them is presented. Hand and object features are extracted from the video sequence using a segmentation based approach. A shape based representation is used for both the hand and the object. Experiments show this representation suitable for representing generic shape classes. The action-object correlation over time is then modeled using conditional random fields. Experimental comparison show great improvement in classification rate when the action-object correlation is taken into account, compared to separate classification of manipulation actions and manipulated objects.

  • 322.
    Kobetski, Miroslav
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Sullivan, Josephine
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Apprenticeship learning: Transfer of knowledge via dataset augmentation2013Ingår i: Image Analysis: 18th Scandinavian Conference, SCIA 2013, Espoo, Finland, June 17-20, 2013. Proceedings, Springer, 2013, 432-443 s.Konferensbidrag (Refereegranskat)
    Abstract [en]

    In visual category recognition there is often a trade-off between fast and powerful classifiers. Complex models often have superior performance to simple ones but are computationally too expensive for many applications. At the same time the performance of simple classifiers is not necessarily limited only by their flexibility but also by the amount of labelled data available for training. We propose a semi-supervised wrapper algorithm named apprenticeship learning, which leverages the strength of slow but powerful classification methods to improve the performance of simpler methods. The powerful classifier parses a large pool of unlabelled data, labelling positive examples to extend the dataset of the simple classifier. We demonstrate apprenticeship learning and its effectiveness by performing experiments on the VOC2007 dataset - one experiment improving detection performance on VOC2007, and one domain adaptation experiment, where the VOC2007 classifier is adapted to a new dataset, collected using a GoPro camera.

  • 323.
    Kobetski, Miroslav
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Sullivan, Josephine
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Discriminative tree-based feature mapping2013Ingår i: BMVC 2013 - Electronic Proceedings of the British Machine Vision Conference 2013, British Machine Vision Association, BMVA , 2013Konferensbidrag (Refereegranskat)
    Abstract [en]

    For object classification and detection, the algorithm pipeline often involves classifying feature vectors extracted from image patches. Existing features such as HOG, fail to map the image patches into a space where a linear hyperplane is suitable for separating the classes, while many non-linear classification methods are too expensive for many tasks. We propose a sparse tree-based mapping method that learns a mapping of the feature vector to a space where a linear hyperplane can better separate negative and positive examples. The learned mapping function Φ(x) results in significant improvement for image patch classification with HOG and LBP-features over other feature mapping methods on VOC2007 and INRIAPerson datasets.

  • 324.
    Kobetski, Miroslav
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Sullivan, Josephine
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Improved boosting performance by exclusion of ambiguous positive examples2013Ingår i: ICPRAM 2013 - Proceedings of the 2nd International Conference on Pattern Recognition Applications and Methods, 2013, 11-21 s.Konferensbidrag (Refereegranskat)
    Abstract [en]

    In visual object class recognition it is difficult to densely sample the set of positive examples. Therefore, frequently there will be areas of the feature space that are sparsely populated, in which uncommon examples are hard to disambiguate from surrounding negatives without overfitting. Boosting in particular struggles to learn optimal decision boundaries in the presence of such hard and ambiguous examples. We propose a two-pass dataset pruning method for identifying ambiguous examples and subjecting them to an exclusion function, in order to obtain more optimal decision boundaries for existing boosting algorithms. We also provide an experimental comparison of different boosting algorithms on the VOC2007 dataset, training them with and without our proposed extension. Using our exclusion extension improves the performance of all the tested boosting algorithms except TangentBoost, without adding any additional test-time cost. In our experiments LogitBoost performs best overall and is also significantly improved by our extension. Our results also suggest that outlier exclusion is complementary to positive jittering and hard negative mining.

  • 325.
    Kobetski, Miroslav
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Sullivan, Josephine
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Improved boosting performance by explicit handling of ambiguous positive examples2015Ingår i: Pattern Recognition: Applications and Methods, Springer Berlin/Heidelberg, 2015, 17-37 s.Konferensbidrag (Refereegranskat)
    Abstract [en]

    Visual classes naturally have ambiguous examples, that are different depending on feature and classifier and are hard to disambiguate from surrounding negatives without overfitting. Boosting in particular tends to overfit to such hard and ambiguous examples, due to its flexibility and typically aggressive loss functions. We propose a two-pass learning method for identifying ambiguous examples and relearning, either subjecting them to an exclusion function or using them in a later stage of an inverted cascade. We provide an experimental comparison of different boosting algorithms on the VOC2007 dataset, training them with and without our proposed extension. Using our exclusion extension improves the performance of almost all of the tested boosting algorithms, without adding any additional test-time cost. Our proposed inverted cascade adds some test-time cost but gives additional improvements in performance. Our results also suggest that outlier exclusion is complementary to positive jittering and hard negative mining.

  • 326.
    Kootstra, Geert
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Wilming, N.
    Schmidt, N. M.
    Djurfeldt, Mikael
    KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Parallelldatorcentrum, PDC.
    Kragic, Danica
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    König, P.
    Learning and adaptation of sensorimotor contingencies: Prism-adaptation, a case study2012Ingår i: From Animals to Animats 12, Springer Berlin/Heidelberg, 2012, Vol. 7426 LNAI, 341-350 s.Konferensbidrag (Refereegranskat)
    Abstract [en]

    This paper focuses on learning and adaptation of sensorimotor contingencies. As a specific case, we investigate the application of prism glasses, which change visual-motor contingencies. After an initial disruption of sensorimotor coordination, humans quickly adapt. However, scope and generalization of that adaptation is highly dependent on the type of feedback and exhibits markedly different degrees of generalization. We apply a model with a specific interaction of forward and inverse models to a robotic setup and subject it to the identical experiments that have been used on previous human psychophysical studies. Our model demonstrates both locally specific adaptation and global generalization in accordance with the psychophysical experiments. These results emphasize the role of the motor system for sensory processes and open an avenue to improve on sensorimotor processing.

  • 327.
    Kootstra, Gert
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Bergström, Niklas
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Kragic, Danica
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Fast and Automatic Detection and Segmentation of Unknown Objects2010Ingår i: Proceedings of the 10th IEEE-RAS International Conference on Humanoid Robots (Humanoids), IEEE , 2010, 442-447 s.Konferensbidrag (Refereegranskat)
    Abstract [en]

    This paper focuses on the fast and automatic detection and segmentation of unknown objects in unknown environments. Many existing object detection and segmentation methods assume prior knowledge about the object or human interference. However, an autonomous system operating in the real world will often be confronted with previously unseen objects. To solve this problem, we propose a segmentation approach named Automatic Detection And Segmentation (ADAS). For the detection of objects, we use symmetry, one of the Gestalt principles for figure-ground segregation to detect salient objects in a scene. From the initial seed, the object is segmented by iteratively applying graph cuts. We base the segmentation on both 2D and 3D cues: color, depth, and plane information. Instead of using a standard grid-based representation of the image, we use super pixels. Besides being a more natural representation, the use of super pixels greatly improves the processing time of the graph cuts, and provides more noise-robust color and depth information. The results show that both the object-detection as well as the object-segmentation method are successful and outperform existing methods.

  • 328.
    Kootstra, Gert
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Bergström, Niklas
    KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS. KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Kragic, Danica
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Gestalt Principles for Attention and Segmentation in Natural and Artificial Vision Systems2011Ingår i: Semantic Perception, Mapping and Exploration (SPME), ICRA 2011 Workshop, eSMCs , 2011Konferensbidrag (Refereegranskat)
    Abstract [en]

    Gestalt psychology studies how the human visual system organizes the complex visual input into unitary elements. In this paper we show how the Gestalt principles for perceptual grouping and for figure-ground segregation can be used in computer vision. A number of studies will be shown that demonstrate the applicability of Gestalt principles for the prediction of human visual attention and for the automatic detection and segmentation of unknown objects by a robotic system.

  • 329.
    Kootstra, Gert
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Bergström, Niklas
    KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS. KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Kragic, Danica
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Using Symmetry to Select Fixation Points for Segmentation2010Ingår i: Proceedings of the 20th International Conference on Pattern Recognition, IEEE , 2010, 3894-3897 s.Konferensbidrag (Refereegranskat)
    Abstract [en]

    For the interpretation of a visual scene, it is important for a robotic system to pay attention to the objects in the scene and segment them from their background. We focus on the segmentation of previously unseen objects in unknown scenes. The attention model therefore needs to be bottom-up and context-free. In this paper, we propose the use of symmetry, one of the Gestalt principles for figure-ground segregation, to guide the robot’s attention. We show that our symmetry-saliency model outperforms the contrast-saliency model, proposed in. The symmetry model performs better in finding the objects of interest and selects a fixation point closer to the center of the object. Moreover, the objects are better segmented from the background when the initial points are selected on the basis of symmetry.

  • 330.
    Kootstra, Gert
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS. KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    de Boer, Bart
    Schomaker, Lambert R. B.
    Predicting Eye Fixations on Complex Visual Stimuli Using Local Symmetry2011Ingår i: Cognitive Computation, ISSN 1866-9956, E-ISSN 1866-9964, Vol. 3, nr 1, 223-240 s.Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Most bottom-up models that predict human eye fixations are based on contrast features. The saliency model of Itti, Koch and Niebur is an example of such contrast-saliency models. Although the model has been successfully compared to human eye fixations, we show that it lacks preciseness in the prediction of fixations on mirror-symmetrical forms. The contrast model gives high response at the borders, whereas human observers consistently look at the symmetrical center of these forms. We propose a saliency model that predicts eye fixations using local mirror symmetry. To test the model, we performed an eye-tracking experiment with participants viewing complex photographic images and compared the data with our symmetry model and the contrast model. The results show that our symmetry model predicts human eye fixations significantly better on a wide variety of images including many that are not selected for their symmetrical content. Moreover, our results show that especially early fixations are on highly symmetrical areas of the images. We conclude that symmetry is a strong predictor of human eye fixations and that it can be used as a predictor of the order of fixation.

  • 331.
    Kootstra, Gert
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Kragic, Danica
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Fast and Bottom-Up Object Detection and Segmentation using Gestalt Principles2011Ingår i: Proceedings of the International Conference on Robotics and Automation (ICRA), IEEE , 2011, 3423-3428 s.Konferensbidrag (Refereegranskat)
    Abstract [en]

    In many scenarios, domestic robot will regularly encounter unknown objects. In such cases, top-down knowledge about the object for detection, recognition, and classification cannot be used. To learn about the object, or to be able to grasp it, bottom-up object segmentation is an important competence for the robot. Also when there is top-down knowledge, prior segmentation of the object can improve recognition and classification. In this paper, we focus on the problem of bottom-up detection and segmentation of unknown objects. Gestalt psychology studies the same phenomenon in human vision. We propose the utilization of a number of Gestalt principles. Our method starts by generating a set of hypotheses about the location of objects using symmetry. These hypotheses are then used to initialize the segmentation process. The main focus of the paper is on the evaluation of the resulting object segments using Gestalt principles to select segments with high figural goodness. The results show that the Gestalt principles can be successfully used for detection and segmentation of unknown objects. The results furthermore indicate that the Gestalt measures for the goodness of a segment correspond well with the objective quality of the segment. We exploit this to improve the overall segmentation performance.

  • 332.
    Kootstra, Gert
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Popovic, Mila
    Jorgensen, Jimmy Alison
    Kuklinski, Kamil
    Miatliuk, Konstantsin
    Kragic, Danica
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Krueger, Norbert
    Enabling grasping of unknown objects through a synergistic use of edge and surface information2012Ingår i: The international journal of robotics research, ISSN 0278-3649, E-ISSN 1741-3176, Vol. 31, nr 10, 1190-1213 s.Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Grasping unknown objects based on visual input, where no a priori knowledge about the objects is used, is a challenging problem. In this paper, we present an Early Cognitive Vision system that builds a hierarchical representation based on edge and texture information which provides a sparse but powerful description of the scene. Based on this representation, we generate contour-based and surface-based grasps. We test our method in two real-world scenarios, as well as on a vision-based grasping benchmark providing a hybrid scenario using real-world stereo images as input and a simulator for extensive and repetitive evaluation of the grasps. The results show that the proposed method is able to generate successful grasps, and in particular that the contour and surface information are complementary for the task of grasping unknown objects. This allows for dealing with rather complex scenes.

  • 333. Kostavelis, I.
    et al.
    Boukas, E.
    Nalpantidis, Lazaros
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Gasteratos, A.
    Path tracing on polar depth maps for robot navigation2012Ingår i: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Springer Berlin/Heidelberg, 2012, 395-404 s.Konferensbidrag (Refereegranskat)
    Abstract [en]

    In this paper a Cellular Automata-based (CA) path estimation algorithm suitable for safe robot navigation is presented. The proposed method combines well established 3D vision techniques with CA operations and traces a collision free route from the foot of the robot to the horizon of a scene. Firstly, the depth map of the scene is obtained and, then, a polar transformation is applied. A v-disparity image calculation processing step is applied to the initial depth map separating the ground plane from the obstacles. In the next step, a CA floor field is formed representing all the distances from the robot to the traversable regions in the scene. The target point that the robot should move towards to, is tracked down and an additional CA routine is applied to the floor field revealing a traversable route that the robot should follow to reach its target location.

  • 334. Kostavelis, I.
    et al.
    Nalpantidis, Lazaros
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Gasteratos, A.
    Collision risk assessment for autonomous robots by offline traversability learning2012Ingår i: Robotics and Autonomous Systems, ISSN 0921-8890, E-ISSN 1872-793X, Vol. 60, nr 11, 1367-1376 s.Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Autonomous robots should be able to move freely in unknown environments and avoid impacts with obstacles. The overall traversability estimation of the terrain and the subsequent selection of an obstacle-free route are prerequisites of a successful autonomous operation. This work proposes a computationally efficient technique for the traversability estimation of the terrain, based on a machine learning classification method. Additionally, a new method for collision risk assessment is introduced. The proposed system uses stereo vision as a first step in order to obtain information about the depth of the scene. Then, a v-disparity image calculation processing step extracts information-rich features about the characteristics of the scene, which are used to train a support vector machine (SVM) separating the traversable and non-traversable scenes. The ones classified as traversable are further processed exploiting the polar transformation of the depth map. The result is a distribution of obstacle existence likelihoods for each direction, parametrized by the robot's embodiment.

  • 335. Kostavelis, I.
    et al.
    Nalpantidis, Lazaros
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Gasteratos, A.
    Object recognition using saliency maps and HTM learning2012Ingår i: Imaging Systems and Techniques (IST), 2012 IEEE International Conference on, IEEE , 2012, 528-532 s.Konferensbidrag (Refereegranskat)
    Abstract [en]

    In this paper a pattern classification and object recognition approach based on bio-inspired techniques is presented. It exploits the Hierarchical Temporal Memory (HTM) topology, which imitates human neocortex for recognition and categorization tasks. The HTM comprises a hierarchical tree structure that exploits enhanced spatiotemporal modules to memorize objects appearing in various orientations. In accordance with HTM's biological inspiration, human vision mechanisms can be used to preprocess the input images. Therefore, the input images undergo a saliency computation step, revealing the plausible information of the scene, where a human might fixate. The adoption of the saliency detection module releases the HTM network from memorizing redundant information and augments the classification accuracy. The efficiency of the proposed framework has been experimentally evaluated in the ETH-80 dataset, and the classification accuracy has been found to be greater than other HTM systems.

  • 336. Kraft, Dirk
    et al.
    Pugeault, Nicolas
    Baseski, Emre
    Popovic, Mila
    Kragic, Danica
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Kalkan, Sinan
    Woergoetter, Florentin
    Krueger, Norbert
    Birth Of The Object: Detection Of Objectness And Extraction Of Object Shape Through Object-Action Complexes2008Ingår i: International Journal of Humanoid Robotics, ISSN 0219-8436, Vol. 5, nr 2, 247-265 s.Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    We describe a process in which the segmentation of objects as well as the extraction of the object shape becomes realized through active exploration of a robot vision system. In the exploration process, two behavioral modules that link robot actions to the visual and haptic perception of objects interact. First, by making use of an object independent grasping mechanism, physical control over potential objects can be gained. Having evaluated the initial grasping mechanism as being successful, a second behavior extracts the object shape by making use of prediction based on the motion induced by the robot. This also leads to the concept of an "object" as a set of features that change predictably over different frames. The system is equipped with a certain degree of generic prior knowledge about the world in terms of a sophisticated visual feature extraction process in an early cognitive vision system, knowledge about its own embodiment as well as knowledge about geometric relationships such as rigid body motion. This prior knowledge allows the extraction of representations that are semantically richer compared to many other approaches.

  • 337. Kraft, Dirk
    et al.
    Pugeault, Nicolas
    Baseski, Emre
    Popovic, Mila
    Kragic, Danica
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Kalkan, Sinan
    Woergoetter, Florentin
    Krueger, Norbert
    BIRTH OF THE OBJECT: DETECTION OF OBJECTNESS AND EXTRACTION OF OBJECT SHAPE THROUGH OBJECT-ACTION COMPLEXES (vol 5, pg 247, 2008)2009Ingår i: International Journal of Humanoid Robotics, ISSN 0219-8436, Vol. 6, nr 3, 561-561 s.Artikel i tidskrift (Refereegranskat)
  • 338.
    Kragic, Danica
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Confluence of parameters in model based tracking2003Konferensbidrag (Refereegranskat)
    Abstract [en]

    During the last decade, model based tracking of objects and its necessity in visual servoing and manipulation has been advocated in a number of systems [4], [7], [9], [12], [13], [14]. Most of these systems demonstrate robust performance for cases where either the background or the object are relatively uniform in color. In terms of manipulation, our basic interest is handling of everyday objects in domestic environments such as a home or an office. In this paper, we consider a number of different parameters that effect the performance of a model-based tracking system. Parameters such as color channels, feature detection, validation gates, outliers rejection and feature selection are considered here and their affect to the overall system performance is discussed. Experimental evaluation shows how some of these parameters can successfully be evaluated (learned) on-line and consequently improve the performance of the system.

  • 339.
    Kragic, Danica
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Robot Visions, Robot Vision2013Ingår i: Twelfth Scandinavian Conference on Artificial Intelligence, 2013, 11-11 s.Konferensbidrag (Refereegranskat)
  • 340.
    Kragic, Danica
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Björkman, Mårten
    KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS. KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Strategies for object manipulation using foveal and peripheral vision2006Ingår i: International Conference on Computer Vision Systems (ICVS), New York, USA, IEEE Computer Society, 2006, 50- s.Konferensbidrag (Refereegranskat)
    Abstract [en]

    Computer vision is gaining significant importance as a cheap, passive, and information-rich sensor in research areas such as unmanned vehicles, medical robotics, human-machine interaction, autonomous navigation,robotic manipulation and grasping. However, a current trend is to build computer vision systems that are used to perform a specific task which makes it hard to reuse the ideas across different disciplines. In this paper, we concentrate on vision strategies for robotic manipulation tasksin a domestic environment. This work is an extension of our ongoing work on a development of a general vision system for robotic applications. Inparticular, given fetch-and-carry type of tasks, the issues related to the whole detect-approach-grasp loop are considered.

  • 341.
    Kragic, Danica
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Björkman, Mårten
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Christensen, Henrik I.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Eklundh, Jan-Olof
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Vision for robotic object manipulation in domestic settings2005Ingår i: Robotics and Autonomous Systems, ISSN 0921-8890, E-ISSN 1872-793X, Vol. 52, nr 1, 85-100 s.Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    In this paper, we present a vision system for robotic object manipulation tasks in natural, domestic environments. Given complex fetch-and-carry robot tasks, the issues related to the whole detect-approach-grasp loop are considered. Our vision system integrates a number of algorithms using monocular and binocular cues to achieve robustness in realistic settings. The cues are considered and used in connection to both foveal and peripheral vision to provide depth information, segmentation of the object(s) of interest, object recognition, tracking and pose estimation. One important property of the system is that the step from object recognition to pose estimation is completely automatic combining both appearance and geometric models. Experimental evaluation is performed in a realistic indoor environment with occlusions, clutter, changing lighting and background conditions.

  • 342.
    Kragic, Danica
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Christensen, Henrik
    KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Robust Visual Servoing2014Ingår i: Household Service Robotics, Elsevier, 2014, 397-427 s.Kapitel i bok, del av antologi (Övrigt vetenskapligt)
    Abstract [en]

    For service robots operating in domestic environments, it is not enough to consider only control level robustness; it is equally important to consider how image information that serves as input to the control process can be used so as to achieve robust and efficient control. In this chapter we present an effort toward the development of robust visual techniques used to guide robots in various tasks. Given a task at hand, we argue that different levels of complexity should be considered; this also defines the choice of the visual technique used to provide the necessary feedback information. We concentrate on visual feedback estimation where we investigate both two- and three-dimensional techniques. In the former case, we are interested in providing coarse information about the object position/velocity in the image plane. In particular, a set of simple visual features (cues) is employed in an integrated framework where voting is used for fusing the responses from individual cues. The experimental evaluation shows the system performance for three different cases of camera-robot configurations most common for robotic systems. For cases where the robot is supposed to grasp the object, a two-dimensional position estimate is often not enough. Complete pose (position and orientation) of the object may be required. Therefore, we present a model-based system where a wire-frame model of the object is used to estimate its pose. Since a number of similar systems have been proposed in literature, we concentrate on the particular part of the system usually neglected-automatic pose initialization. Finally, we show how a number of existing approaches can successfully be integrated in a system that is able to recognize and grasp fairly textured, everyday objects. One of the examples presented in the experimental section shows a mobile robot performing tasks in a real-word environment-a living room.

  • 343.
    Kragic, Danica
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Christensen, Henrik I
    A Framework for Visual Servoing2003Ingår i: International Conference on Computer Vision Systems, Springer-Verlag Berlin , 2003, 345-354 s.Kapitel i bok, del av antologi (Refereegranskat)
    Abstract [en]

    . A general framework for visual servoing tasks is proposed. The objective of the paper is twofold: a) how a complicated servoing task might be composed from a multitude of simple ones, and b) how the integration of basic and simple visual algorithms can be used in order to provide a robust input estimate to a control loop for a mobile platform or a robot manipulator. For that purpose, voting schema and consensus theory approaches are investigated together with some initial vision based algorithms. Voting is known as a model--free approach to integration and therefore interesting for applications in real--world environments which are difficult to model. It is experimentally shown how servoing tasks like pick--and--place, opening doors and fetching mail can be robustly performed using the proposed approach. 1. Introduction In the field of service robotics, robots should continuously interact with objects and human beings in a natural, unstructured and dynamic environment. In ...

  • 344.
    Kragic, Danica
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Christensen, Henrik I.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Advances in robot vision2005Ingår i: Robotics and Autonomous Systems, ISSN 0921-8890, E-ISSN 1872-793X, Vol. 52, nr 1, 1-3 s.Artikel i tidskrift (Övrigt vetenskapligt)
  • 345.
    Kragic, Danica
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Christensen, Henrik I
    Integration of visual cues for active tracking of an end-effector1999Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    We describe and test how information from multiple sources can be combined into a robust visual servoing system. The main objective is integration of visual cues to provide smooth pursuit in a cluttered environment using a minimum or no calibration. For that purpose, voting schema and fuzzy logic command fusion are investigated. It is shown that the integration permits detection and rejection of measurement outliers

  • 346.
    Kragic, Danica
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Christensen, Henrik I
    Model Based Techniques for Robotic Servoing and Grasping2002Konferensbidrag (Refereegranskat)
    Abstract [en]

     A robotic manipulation of objects typically involves object detection/recognition, servoing to the object, alignment and grasping. To perform fine alignment and finally grasping, it is usually necessary to estimate position and orientation (pose) of the object. In this paper we present a model based tracking system used to estimate and continuously update the pose of the object to be manipulated. Here, a wire-frame model is used to find and track features in the consequent images. One of the important parts of the system is the ability to automatically initiate the tracking process. The strength of the system is the ability to operate in an domestic environment (living room) with changing lighting and background conditions.

  • 347.
    Kragic, Danica
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Christensen, Henrik I
    Survey on Visual Servoing for Manipulation2002Konferensbidrag (Refereegranskat)
    Abstract [en]

    Vision guided robotics has been one of the major research issue for more than three decades. The more recent technological development facilitated the advancement in the area which has resulted in a number of successful and even commercial systems using off–the–shelf hardware. The applications of visually guided systems are many: from intelligent homes to automotive industry. However, one of the open and commonly stated problems in the area is the need for exchange of experiences and research ideas. In our opinion, a good starting point for this is to advertise the successes and propose a common terminology in form of a survey paper. The paper concentrates on different types of visual servoing: image based, position based and 2 1/2D visual servoing. Different issues concerning both the hardware and software requirements are considered and the most prominent contributions are reviewed. The proposed terminology is used to introduce a young researcher and lead the experts in the field through a three decades long historical field of vision guided robotics. We also include a number of real–world examples from our own research providing not only a conceptual framework but also illustrating most of the issues covered in the paper.

  • 348.
    Kragic, Danica
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Christensen, Henrik I
    Tracking Techniques for Visual Servoing Tasks2000Konferensbidrag (Refereegranskat)
    Abstract [en]

    Many of today's visual servoing systems rely on the use of markers on the object to provide features for control. There is thus a need for a visual system that provides control features regardless of the appearance of the object. Region based tracking is a natural approach since it does not require any special type of features. In this paper we present two different approaches to region based tracking: 1) a multi-resolution gradient based approach (using optical flow); and 2) a discrete feature based search approach. We present experiments conducted with both techniques for different types of image motions. Finally, the performance, drawbacks and limitations of used techniques are discussed

  • 349.
    Kragic, Danica
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Christensen, Henrik I
    Using a redundant coarsely calibrated vision system for 3d grasping1999Konferensbidrag (Refereegranskat)
    Abstract [en]

    The influence of a redundant camera system for estimation of 3D object position and orientation in a manipulator´s workspace is analysed. The paper analyses the accuracy that can be achieved using a trinocular stereo system, that only has been qualiatively calibrated.  By using stereo combined with a third camera a significant improvment in accuracy is achieved. An experimental system, which exploits colour and Hough transform for object pose estimation, is used for empirical assessment of accuracy in the context of object grasping.

  • 350.
    Kragic, Danica
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Christensen, Henrik I
    Weak Models and Cue Integration for Real-Time Tracking2002Konferensbidrag (Refereegranskat)
    Abstract [en]

    Traditionally, fusion of visual information for tracking has been based on explicit models for uncertainty and integration. Most of the approaches use some form of Bayesian statistics where strong models are employed. We argue that for cases where a large number of visual features are available, weak models for integration may be employed. We analyze integration by voting where two methods are proposed and evaluated: i) response and ii) action fusion. The methods differ in the choice of Voting space: the former integrates visual information in image space and latter in velocity space. We also evaluate four weighting techniques for integration.

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