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  • 1. Abbeloos, W.
    et al.
    Caccamo, Sergio
    KTH, Skolan för datavetenskap och kommunikation (CSC), Robotik, perception och lärande, RPL.
    Ataer-Cansizoglu, E.
    Taguchi, Y.
    Feng, C.
    Lee, T. -Y
    Detecting and Grouping Identical Objects for Region Proposal and Classification2017Inngår i: 2017 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, IEEE Computer Society, 2017, Vol. 2017, s. 501-502, artikkel-id 8014810Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Often multiple instances of an object occur in the same scene, for example in a warehouse. Unsupervised multi-instance object discovery algorithms are able to detect and identify such objects. We use such an algorithm to provide object proposals to a convolutional neural network (CNN) based classifier. This results in fewer regions to evaluate, compared to traditional region proposal algorithms. Additionally, it enables using the joint probability of multiple instances of an object, resulting in improved classification accuracy. The proposed technique can also split a single class into multiple sub-classes corresponding to the different object types, enabling hierarchical classification.

  • 2.
    Abedin, Md Reaz Ashraful
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Bensch, Suna
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Hellström, Thomas
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Self-supervised language grounding by active sensing combined with Internet acquired images and text2017Inngår i: Proceedings of the Fourth International Workshop on Recognition and Action for Scene Understanding (REACTS2017) / [ed] Jorge Dias George Azzopardi, Rebeca Marf, Málaga: REACTS , 2017, s. 71-83Konferansepaper (Fagfellevurdert)
    Abstract [en]

    For natural and efficient verbal communication between a robot and humans, the robot should be able to learn names and appearances of new objects it encounters. In this paper we present a solution combining active sensing of images with text based and image based search on the Internet. The approach allows the robot to learn both object name and how to recognise similar objects in the future, all self-supervised without human assistance. One part of the solution is a novel iterative method to determine the object name using image classi- fication, acquisition of images from additional viewpoints, and Internet search. In this paper, the algorithmic part of the proposed solution is presented together with evaluations using manually acquired camera images, while Internet data was acquired through direct and reverse image search with Google, Bing, and Yandex. Classification with multi-classSVM and with five different features settings were evaluated. With five object classes, the best performing classifier used a combination of Pyramid of Histogram of Visual Words (PHOW) and Pyramid of Histogram of Oriented Gradient (PHOG) features, and reached a precision of 80% and a recall of 78%.

  • 3. Abela, D
    et al.
    Ritchie, H
    Ababneh, D
    Gavin, C
    Nilsson, Mats F
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Farmaceutiska fakulteten, Institutionen för farmaceutisk biovetenskap.
    Niazi, M Khalid Khan
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Centrum för bildanalys.
    Carlsson, K
    Webster, WS
    The effect of drugs with ion channel-blocking activity on the early embryonic rat heart2010Inngår i: Birth defects research. Part B. Developmental and reproductice toxicology, ISSN 1542-9733, E-ISSN 1542-9741, Vol. 89, nr 5, s. 429-440Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    This study investigated the effects of a range of pharmaceutical drugs with ion channel-blocking activity on the heart of gestation day 13 rat embryos in vitro. The general hypothesis was that the blockade of the IKr/hERG channel, that is highly important for the normal functioning of the embryonic rat heart, would cause bradycardia and arrhythmia. Concomitant blockade of other channels was expected to modify the effects of hERG blockade. Fourteen drugs with varying degrees of specificity and affinity toward potassium, sodium, and calcium channels were tested over a range of concentrations. The rat embryos were maintained for 2 hr in culture, 1 hr to acclimatize, and 1 hr to test the effect of the drug. All the drugs caused a concentration-dependent bradycardia except nifedipine, which primarily caused a negative inotropic effect eventually stopping the heart. A number of drugs induced arrhythmias and these appeared to be related to either sodium channel blockade, which resulted in a double atrial beat for each ventricular beat, or IKr/hERG blockade, which caused irregular atrial and ventricular beats. However, it is difficult to make a precise prediction of the effect of a drug on the embryonic heart just by looking at the polypharmacological action on ion channels. The results indicate that the use of the tested drugs during pregnancy could potentially damage the embryo by causing periods of hypoxia. In general, the effects on the embryonic heart were only seen at concentrations greater than those likely to occur with normal therapeutic dosing.

  • 4. Abeywardena, D.
    et al.
    Wang, Zhan
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Dissanayake, G.
    Waslander, S. L.
    Kodagoda, S.
    Model-aided state estimation for quadrotor micro air vehicles amidst wind disturbances2014Konferansepaper (Fagfellevurdert)
    Abstract [en]

    This paper extends the recently developed Model-Aided Visual-Inertial Fusion (MA-VIF) technique for quadrotor Micro Air Vehicles (MAV) to deal with wind disturbances. The wind effects are explicitly modelled in the quadrotor dynamic equations excluding the unobservable wind velocity component. This is achieved by a nonlinear observability of the dynamic system with wind effects. We show that using the developed model, the vehicle pose and two components of the wind velocity vector can be simultaneously estimated with a monocular camera and an inertial measurement unit. We also show that the MA-VIF is reasonably tolerant to wind disturbances, even without explicit modelling of wind effects and explain the reasons for this behaviour. Experimental results using a Vicon motion capture system are presented to demonstrate the effectiveness of the proposed method and validate our claims.

  • 5.
    Abrate, Matteo
    et al.
    CNR Natl Res Council, Inst Informat & Telemat, I-56124 Pisa, Italy.
    Bacciu, Clara
    CNR Natl Res Council, Inst Informat & Telemat, I-56124 Pisa, Italy.
    Hast, Anders
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion. CNR Natl Res Council, Inst Informat & Telemat, I-56124 Pisa, Italy.
    Marchetti, Andrea
    CNR Natl Res Council, Inst Informat & Telemat, I-56124 Pisa, Italy.
    Minutoli, Salvatore
    CNR Natl Res Council, Inst Informat & Telemat, I-56124 Pisa, Italy.
    Tesconi, Maurizio
    CNR Natl Res Council, Inst Informat & Telemat, I-56124 Pisa, Italy.
    Geomemories - A Platform for Visualizing Historical, Environmental and Geospatial Changes of the Italian Landscape2013Inngår i: ISPRS International Journal of Geo-Information. Special issue: Geospatial Monitoring and Modelling of Environmental Change, ISSN 2220-9964, Vol. 2, nr 2, s. 432-455Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    The GeoMemories project aims at publishing on the Web and digitally preserving historical aerial photographs that are currently stored in physical form within the archives of the Aerofototeca Nazionale in Rome. We describe a system, available at http://www.geomemories.org, that lets users visualize the evolution of the Italian landscape throughout the last century. The Web portal allows comparison of recent satellite imagery with several layers of historical maps, obtained from the aerial photos through a complex workflow that merges them together. We present several case studies carried out in collaboration with geologists, historians and archaeologists, that illustrate the great potential of our system in different research fields. Experiments and advances in image processing technologies are envisaged as a key factor in solving the inherent issue of vast amounts of manual work, from georeferencing to mosaicking to analysis.

  • 6. Adinugroho, Sigit
    et al.
    Vallot, Dorothée
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Geovetenskapliga sektionen, Institutionen för geovetenskaper, Luft-, vatten och landskapslära.
    Westrin, Pontus
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Geovetenskapliga sektionen, Institutionen för geovetenskaper.
    Strand, Robin
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Calving events detection and quantification from time-lapse images in Tunabreen glacier2015Inngår i: Proc. 9th International Conference on Information & Communication Technology and Systems, Piscataway, NJ: IEEE , 2015, s. 61-65Konferansepaper (Fagfellevurdert)
  • 7.
    Adler, Jonas
    et al.
    KTH, Skolan för teknikvetenskap (SCI), Matematik (Inst.), Matematik (Avd.). Elekta Instrument AB, Stockholm, Sweden.
    Öktem, Ozan
    KTH, Skolan för teknikvetenskap (SCI), Matematik (Inst.), Matematik (Avd.).
    Learned Primal-Dual Reconstruction2018Inngår i: IEEE Transactions on Medical Imaging, ISSN 0278-0062, E-ISSN 1558-254X, Vol. 37, nr 6, s. 1322-1332Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    We propose the Learned Primal-Dual algorithm for tomographic reconstruction. The algorithm accounts for a (possibly non-linear) forward operator in a deep neural network by unrolling a proximal primal-dual optimization method, but where the proximal operators have been replaced with convolutional neural networks. The algorithm is trained end-to-end, working directly from raw measured data and it does not depend on any initial reconstruction such as filtered back-projection (FBP). We compare performance of the proposed method on low dose computed tomography reconstruction against FBP, total variation (TV), and deep learning based post-processing of FBP. For the Shepp-Logan phantom we obtain >6 dB peak signal to noise ratio improvement against all compared methods. For human phantoms the corresponding improvement is 6.6 dB over TV and 2.2 dB over learned post-processing along with a substantial improvement in the structural similarity index. Finally, our algorithm involves only ten forward-back-projection computations, making the method feasible for time critical clinical applications.

  • 8.
    Aghazadeh, Omid
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Data Driven Visual Recognition2014Doktoravhandling, med artikler (Annet vitenskapelig)
    Abstract [en]

    This thesis is mostly about supervised visual recognition problems. Based on a general definition of categories, the contents are divided into two parts: one which models categories and one which is not category based. We are interested in data driven solutions for both kinds of problems.

    In the category-free part, we study novelty detection in temporal and spatial domains as a category-free recognition problem. Using data driven models, we demonstrate that based on a few reference exemplars, our methods are able to detect novelties in ego-motions of people, and changes in the static environments surrounding them.

    In the category level part, we study object recognition. We consider both object category classification and localization, and propose scalable data driven approaches for both problems. A mixture of parametric classifiers, initialized with a sophisticated clustering of the training data, is demonstrated to adapt to the data better than various baselines such as the same model initialized with less subtly designed procedures. A nonparametric large margin classifier is introduced and demonstrated to have a multitude of advantages in comparison to its competitors: better training and testing time costs, the ability to make use of indefinite/invariant and deformable similarity measures, and adaptive complexity are the main features of the proposed model.

    We also propose a rather realistic model of recognition problems, which quantifies the interplay between representations, classifiers, and recognition performances. Based on data-describing measures which are aggregates of pairwise similarities of the training data, our model characterizes and describes the distributions of training exemplars. The measures are shown to capture many aspects of the difficulty of categorization problems and correlate significantly to the observed recognition performances. Utilizing these measures, the model predicts the performance of particular classifiers on distributions similar to the training data. These predictions, when compared to the test performance of the classifiers on the test sets, are reasonably accurate.

    We discuss various aspects of visual recognition problems: what is the interplay between representations and classification tasks, how can different models better adapt to the training data, etc. We describe and analyze the aforementioned methods that are designed to tackle different visual recognition problems, but share one common characteristic: being data driven.

  • 9.
    Aghazadeh, Omid
    et al.
    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.
    Carlsson, Stefan
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Mixture component identification and learning for visual recognition2012Inngår i: Computer Vision – ECCV 2012: 12th European Conference on Computer Vision, Florence, Italy, October 7-13, 2012, Proceedings, Part VI, Springer, 2012, s. 115-128Konferansepaper (Fagfellevurdert)
    Abstract [en]

    The non-linear decision boundary between object and background classes - due to large intra-class variations - needs to be modelled by any classifier wishing to achieve good results. While a mixture of linear classifiers is capable of modelling this non-linearity, learning this mixture from weakly annotated data is non-trivial and is the paper's focus. Our approach is to identify the modes in the distribution of our positive examples by clustering, and to utilize this clustering in a latent SVM formulation to learn the mixture model. The clustering relies on a robust measure of visual similarity which suppresses uninformative clutter by using a novel representation based on the exemplar SVM. This subtle clustering of the data leads to learning better mixture models, as is demonstrated via extensive evaluations on Pascal VOC 2007. The final classifier, using a HOG representation of the global image patch, achieves performance comparable to the state-of-the-art while being more efficient at detection time.

  • 10.
    Aghazadeh, Omid
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Carlsson, Stefan
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Large Scale, Large Margin Classification using Indefinite Similarity MeasurensManuskript (preprint) (Annet vitenskapelig)
  • 11.
    Aghazadeh, Omid
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Carlsson, Stefan
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Properties of Datasets Predict the Performance of Classifiers2013Inngår i: BMVC 2013 - Electronic Proceedings of the British Machine Vision Conference 2013, British Machine Vision Association, BMVA , 2013Konferansepaper (Fagfellevurdert)
    Abstract [en]

    It has been shown that the performance of classifiers depends not only on the number of training samples, but also on the quality of the training set [10, 12]. The purpose of this paper is to 1) provide quantitative measures that determine the quality of the training set and 2) provide the relation between the test performance and the proposed measures. The measures are derived from pairwise affinities between training exemplars of the positive class and they have a generative nature. We show that the performance of the state of the art methods, on the test set, can be reasonably predicted based on the values of the proposed measures on the training set. These measures open up a wide range of applications to the recognition community enabling us to analyze the behavior of the learning algorithms w.r.t the properties of the training data. This will in turn enable us to devise rules for the automatic selection of training data that maximize the quantified quality of the training set and thereby improve recognition performance.

  • 12.
    Aghazadeh, Omid
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Carlsson, Stefan
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Properties of Datasets Predict the Performance of Classifiers2013Manuskript (preprint) (Annet vitenskapelig)
  • 13.
    Aghazadeh, Omid
    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.
    Carlsson, Stefan
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Multi view registration for novelty/background separation2012Inngår i: Computer Vision and Pattern Recognition (CVPR), 2012 IEEE Conference on, IEEE Computer Society, 2012, s. 757-764Konferansepaper (Fagfellevurdert)
    Abstract [en]

    We propose a system for the automatic segmentation of novelties from the background in scenarios where multiple images of the same environment are available e.g. obtained by wearable visual cameras. Our method finds the pixels in a query image corresponding to the underlying background environment by comparing it to reference images of the same scene. This is achieved despite the fact that all the images may have different viewpoints, significantly different illumination conditions and contain different objects cars, people, bicycles, etc. occluding the background. We estimate the probability of each pixel, in the query image, belonging to the background by computing its appearance inconsistency to the multiple reference images. We then, produce multiple segmentations of the query image using an iterated graph cuts algorithm, initializing from these estimated probabilities and consecutively combine these segmentations to come up with a final segmentation of the background. Detection of the background in turn highlights the novel pixels. We demonstrate the effectiveness of our approach on a challenging outdoors data set.

  • 14.
    Agrawal, Vikas
    et al.
    IBM Research, , India.
    Archibald, Christopher
    Mississippi State University, Starkville, United States.
    Bhatt, Mehul
    University of Bremen, Bremen, Germany.
    Bui, Hung Hai
    Laboratory for Natural Language Understanding, Sunnyvale CA, United States.
    Cook, Diane J.
    Washington State University, Pullman WA, United States.
    Cortés, Juan
    University of Toulouse, Toulouse, France.
    Geib, Christopher W.
    Drexel University, Philadelphia PA, United States.
    Gogate, Vibhav
    Department of Computer Science, University of Texas, Dallas, United States.
    Guesgen, Hans W.
    Massey University, Palmerston North, New Zealand.
    Jannach, Dietmar
    Technical university Dortmund, Dortmund, Germany.
    Johanson, Michael
    University of Alberta, Edmonton, Canada.
    Kersting, Kristian
    Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme (IAIS), Sankt Augustin, Germany; The University of Bonn, Bonn, Germany.
    Konidaris, George
    Massachusetts Institute of Technology (MIT), Cambridge MA, United States.
    Kotthoff, Lars
    INSIGHT Centre for Data Analytics, University College Cork, Cork, Ireland.
    Michalowski, Martin
    Adventium Labs, Minneapolis MN, United States.
    Natarajan, Sriraam
    Indiana University, Bloomington IN, United States.
    O’Sullivan, Barry
    INSIGHT Centre for Data Analytics, University College Cork, Cork, Ireland.
    Pickett, Marc
    Naval Research Laboratory, Washington DC, United States.
    Podobnik, Vedran
    Telecommunication Department of the Faculty of Electrical Engineering and Computing, University of University of Zagreb, Zagreb, Croatia.
    Poole, David
    Department of Computer Science, University of British Columbia, Vancouver, Canada.
    Shastri, Lokendra
    Infosys, , India.
    Shehu, Amarda
    George Mason University, Washington, United States.
    Sukthankar, Gita
    University of Central Florida, Orlando FL, United States.
    The AAAI-13 Conference Workshops2013Inngår i: The AI Magazine, ISSN 0738-4602, Vol. 34, nr 4, s. 108-115Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    The AAAI-13 Workshop Program, a part of the 27th AAAI Conference on Artificial Intelligence, was held Sunday and Monday, July 14-15, 2013, at the Hyatt Regency Bellevue Hotel in Bellevue, Washington, USA. The program included 12 workshops covering a wide range of topics in artificial intelligence, including Activity Context-Aware System Architectures (WS-13-05); Artificial Intelligence and Robotics Methods in Computational Biology (WS-13-06); Combining Constraint Solving with Mining and Learning (WS-13-07); Computer Poker and Imperfect Information (WS-13-08); Expanding the Boundaries of Health Informatics Using Artificial Intelligence (WS-13-09); Intelligent Robotic Systems (WS-13-10); Intelligent Techniques for Web Personalization and Recommendation (WS-13-11); Learning Rich Representations from Low-Level Sensors (WS-13-12); Plan, Activity,, and Intent Recognition (WS-13-13); Space, Time, and Ambient Intelligence (WS-13-14); Trading Agent Design and Analysis (WS-13-15); and Statistical Relational Artificial Intelligence (WS-13-16)

  • 15.
    Ahlberg, Jörgen
    et al.
    Linköpings universitet, Institutionen för systemteknik, Datorseende. Linköpings universitet, Tekniska fakulteten.
    Arsic, Dejan
    Munich University of Technology, Germany.
    Ganchev, Todor
    University of Patras, Greece.
    Linderhed, Anna
    FOI Swedish Defence Research Agency.
    Menezes, Paolo
    University of Coimbra, Portugal.
    Ntalampiras, Stavros
    University of Patras, Greece.
    Olma, Tadeusz
    MARAC S.A., Greece.
    Potamitis, Ilyas
    Technological Educational Institute of Crete, Greece.
    Ros, Julien
    Probayes SAS, France.
    Prometheus: Prediction and interpretation of human behaviour based on probabilistic structures and heterogeneous sensors2008Konferansepaper (Fagfellevurdert)
    Abstract [en]

    The on-going EU funded project Prometheus (FP7-214901) aims at establishing a general framework which links fundamental sensing tasks to automated cognition processes enabling interpretation and short-term prediction of individual and collective human behaviours in unrestricted environments as well as complex human interactions. To achieve the aforementioned goals, the Prometheus consortium works on the following core scientific and technological objectives:

    1. sensor modeling and information fusion from multiple, heterogeneous perceptual modalities;

    2. modeling, localization, and tracking of multiple people;

    3. modeling, recognition, and short-term prediction of continuous complex human behavior.

  • 16.
    Ahlberg, Jörgen
    et al.
    Linköpings universitet, Institutionen för systemteknik, Informationskodning. Linköpings universitet, Institutionen för systemteknik, Datorseende. Linköpings universitet, Tekniska fakulteten. Termisk Systemteknik AB, Linköping, Sweden.
    Berg, Amanda
    Linköpings universitet, Institutionen för systemteknik, Datorseende. Linköpings universitet, Tekniska fakulteten. Termisk Systemteknik AB, Linköping, Sweden.
    Evaluating Template Rescaling in Short-Term Single-Object Tracking2015Konferansepaper (Fagfellevurdert)
    Abstract [en]

    In recent years, short-term single-object tracking has emerged has a popular research topic, as it constitutes the core of more general tracking systems. Many such tracking methods are based on matching a part of the image with a template that is learnt online and represented by, for example, a correlation filter or a distribution field. In order for such a tracker to be able to not only find the position, but also the scale, of the tracked object in the next frame, some kind of scale estimation step is needed. This step is sometimes separate from the position estimation step, but is nevertheless jointly evaluated in de facto benchmarks. However, for practical as well as scientific reasons, the scale estimation step should be evaluated separately – for example,theremightincertainsituationsbeothermethodsmore suitable for the task. In this paper, we describe an evaluation method for scale estimation in template-based short-term single-object tracking, and evaluate two state-of-the-art tracking methods where estimation of scale and position are separable.

  • 17.
    Ahlberg, Jörgen
    et al.
    Swedish Defence Research Agency (FOI), Linköping, Sweden.
    Dornaika, Fadi
    Linköpings universitet, Institutionen för systemteknik, Bildkodning. Linköpings universitet, Tekniska högskolan.
    Efficient active appearance model for real-time head and facial feature tracking2003Inngår i: Analysis and Modeling of Faces and Gestures, 2003. AMFG 2003. IEEE International Workshop on, IEEE conference proceedings, 2003, s. 173-180Konferansepaper (Fagfellevurdert)
    Abstract [en]

    We address the 3D tracking of pose and animation of the human face in monocular image sequences using active appearance models. The classical appearance-based tracking suffers from two disadvantages: (i) the estimated out-of-plane motions are not very accurate, and (ii) the convergence of the optimization process to desired minima is not guaranteed. We aim at designing an efficient active appearance model, which is able to cope with the above disadvantages by retaining the strengths of feature-based and featureless tracking methodologies. For each frame, the adaptation is split into two consecutive stages. In the first stage, the 3D head pose is recovered using robust statistics and a measure of consistency with a statistical model of a face texture. In the second stage, the local motion associated with some facial features is recovered using the concept of the active appearance model search. Tracking experiments and method comparison demonstrate the robustness and out-performance of the developed framework.

  • 18.
    Ahlberg, Jörgen
    et al.
    Dept. of IR Systems, Div. of Sensor Technology, Swedish Defence Research Agency (FOI), Linköping, Sweden.
    Dornaika, Fadi
    Computer Vision Center, Universitat Autonoma de Barcelona, Bellaterra, Spain.
    Parametric Face Modeling and Tracking2005Inngår i: Handbook of Face Recognition / [ed] Stan Z. Li, Anil K. Jain, Springer-Verlag New York, 2005, s. 65-87Kapittel i bok, del av antologi (Annet vitenskapelig)
  • 19.
    Ahlberg, Jörgen
    et al.
    Linköpings universitet, Institutionen för systemteknik, Bildkodning. Linköpings universitet, Tekniska högskolan. Div. of Sensor Technology, Swedish Defence Research Agency, Linköping, Sweden.
    Forchheimer, Robert
    Linköpings universitet, Institutionen för systemteknik, Bildkodning. Linköpings universitet, Tekniska högskolan.
    Face tracking for model-based coding and face animation2003Inngår i: International journal of imaging systems and technology (Print), ISSN 0899-9457, E-ISSN 1098-1098, Vol. 13, nr 1, s. 8-22Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    We present a face and facial feature tracking system able to extract animation parameters describing the motion and articulation of a human face in real-time on consumer hardware. The system is based on a statistical model of face appearance and a search algorithm for adapting the model to an image. Speed and robustness is discussed, and the system evaluated in terms of accuracy.

  • 20.
    Ahlberg, Jörgen
    et al.
    Div. of Sensor Technology, Swedish Defence Research Agency (FOI), Linköping, Sweden.
    Klasén, Lena
    Div. of Sensor Technology, Swedish Defence Research Agency (FOI), Linköping, Sweden.
    Surveillance Systems for Urban Crisis Management2005Konferansepaper (Annet vitenskapelig)
    Abstract [en]

    We present a concept for combing 3D models and multiple heterogeneous sensors into a surveillance system enabling superior situation awareness. The concept has many military as well as civilian applications. A key issue is the use of a 3D environment model of the area to be surveyed, typically an urban area. In addition to the 3D model, the area of interest is monitored over time using multiple heterogeneous sensors, such as optical, acoustic, and/or seismic sensors. Data and analysis results from the sensors are visualized in the 3D model, thus putting them in a common reference frame and making their spatial and temporal relations obvious. The result is highlighted by an example where data from different sensor systems is integrated in a 3D model of a Swedish urban area.

  • 21.
    Ahlberg, Jörgen
    et al.
    Termisk Systemteknik AB Linköping, Sweden; Visage Technologies AB Linköping, Sweden.
    Markuš, Nenad
    Human-Oriented Technologies Laboratory, Faculty of Electrical Engineering and Computing, University of Zagreb, Croatia.
    Berg, Amanda
    Termisk Systemteknik AB, Linköping, Sweden.
    Multi-person fever screening using a thermal and a visual camera2015Konferansepaper (Annet vitenskapelig)
    Abstract [en]

    We propose a system to automatically measure the body temperature of persons as they pass. In contrast to exisitng systems, the persons do not need to stop and look into a camera one-by-one. Instead, their eye corners are automatically detected and the temperatures therein measured using a thermal camera. The system handles multiple simultaneous persons and can thus be used where a flow of people pass, such as at airport gates.

  • 22.
    Ahlberg, Jörgen
    et al.
    Linköpings universitet, Institutionen för systemteknik, Datorseende. Linköpings universitet, Tekniska fakulteten. Glana Sensors AB, Sweden.
    Renhorn, Ingmar
    Glana Sensors AB, Sweden.
    Chevalier, Tomas
    Scienvisic AB, Sweden.
    Rydell, Joakim
    FOI, Swedish Defence Research Agency, Sweden.
    Bergström, David
    FOI, Swedish Defence Research Agency, Sweden.
    Three-dimensional hyperspectral imaging technique2017Inngår i: ALGORITHMS AND TECHNOLOGIES FOR MULTISPECTRAL, HYPERSPECTRAL, AND ULTRASPECTRAL IMAGERY XXIII / [ed] Miguel Velez-Reyes; David W. Messinger, SPIE - International Society for Optical Engineering, 2017, Vol. 10198, artikkel-id 1019805Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Hyperspectral remote sensing based on unmanned airborne vehicles is a field increasing in importance. The combined functionality of simultaneous hyperspectral and geometric modeling is less developed. A configuration has been developed that enables the reconstruction of the hyperspectral three-dimensional (3D) environment. The hyperspectral camera is based on a linear variable filter and a high frame rate, high resolution camera enabling point-to-point matching and 3D reconstruction. This allows the information to be combined into a single and complete 3D hyperspectral model. In this paper, we describe the camera and illustrate capabilities and difficulties through real-world experiments.

  • 23.
    Ahlberg, Jörgen
    et al.
    Swedish Defence Research Agency (FOI), Linköping, Sweden.
    Renhorn, Ingmar G.
    Swedish Defence Research Agency (FOI), Linköping, Sweden.
    Wadströmer, Niclas
    Swedish Defence Research Agency (FOI), Linköping, Sweden.
    An information measure of sensor performance and its relation to the ROC curve2010Inngår i: Proc. SPIE 7695, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVI / [ed] Sylvia S. Shen; Paul E. Lewis, SPIE - International Society for Optical Engineering, 2010, s. Art.nr. 7695-72-Konferansepaper (Fagfellevurdert)
    Abstract [en]

    The ROC curve is the most frequently used performance measure for detection methods and the underlying sensor configuration. Common problems are that the ROC curve does not present a single number that can be compared to other systems and that no discrimination between sensor performance and algorithm performance is done. To address the first problem, a number of measures are used in practice, like detection rate at a specific false alarm rate, or area-under-curve. For the second problem, we proposed in a previous paper1 an information theoretic method for measuring sensor performance. We now relate the method to the ROC curve, show that it is equivalent to selecting a certain point on the ROC curve, and that this point is easily determined. Our scope is hyperspectral data, studying discrimination between single pixels.

  • 24.
    Ahlman, Gustav
    Linköpings universitet, Institutionen för systemteknik, Datorseende.
    Improved Temporal Resolution Using Parallel Imaging in Radial-Cartesian 3D functional MRI2011Independent thesis Advanced level (degree of Master (Two Years)), 20 poäng / 30 hpOppgave
    Abstract [en]

    MRI (Magnetic Resonance Imaging) is a medical imaging method that uses magnetic fields in order to retrieve images of the human body. This thesis revolves around a novel acquisition method of 3D fMRI (functional Magnetic Resonance Imaging) called PRESTO-CAN that uses a radial pattern in order to sample the (kx,kz)-plane of k-space (the frequency domain), and a Cartesian sample pattern in the ky-direction. The radial sample pattern allows for a denser sampling of the central parts of k-space, which contain the most basic frequency information about the structure of the recorded object. This allows for higher temporal resolution to be achieved compared with other sampling methods since a fewer amount of total samples are needed in order to retrieve enough information about how the object has changed over time. Since fMRI is mainly used for monitoring blood flow in the brain, increased temporal resolution means that we can be able to track fast changes in brain activity more efficiently.The temporal resolution can be further improved by reducing the time needed for scanning, which in turn can be achieved by applying parallel imaging. One such parallel imaging method is SENSE (SENSitivity Encoding). The scan time is reduced by decreasing the sampling density, which causes aliasing in the recorded images. The aliasing is removed by the SENSE method by utilizing the extra information provided by the fact that multiple receiver coils with differing sensitivities are used during the acquisition. By measuring the sensitivities of the respective receiver coils and solving an equation system with the aliased images, it is possible to calculate how they would have looked like without aliasing.In this master thesis, SENSE has been successfully implemented in PRESTO-CAN. By using normalized convolution in order to refine the sensitivity maps of the receiver coils, images with satisfying quality was able to be reconstructed when reducing the k-space sample rate by a factor of 2, and images of relatively good quality also when the sample rate was reduced by a factor of 4. In this way, this thesis has been able to contribute to the improvement of the temporal resolution of the PRESTO-CAN method.

  • 25.
    Ahtiainen, Juhana