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  • 1.
    Abedan Kondori, Farid
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för tillämpad fysik och elektronik.
    Bring Your Body into Action: Body Gesture Detection, Tracking, and Analysis for Natural Interaction2014Doktorsavhandling, sammanläggning (Övrigt vetenskapligt)
    Abstract [en]

    Due to the large influx of computers in our daily lives, human-computer interaction has become crucially important. For a long time, focusing on what users need has been critical for designing interaction methods. However, new perspective tends to extend this attitude to encompass how human desires, interests, and ambitions can be met and supported. This implies that the way we interact with computers should be revisited. Centralizing human values rather than user needs is of the utmost importance for providing new interaction techniques. These values drive our decisions and actions, and are essential to what makes us human. This motivated us to introduce new interaction methods that will support human values, particularly human well-being.

    The aim of this thesis is to design new interaction methods that will empower human to have a healthy, intuitive, and pleasurable interaction with tomorrow’s digital world. In order to achieve this aim, this research is concerned with developing theories and techniques for exploring interaction methods beyond keyboard and mouse, utilizing human body. Therefore, this thesis addresses a very fundamental problem, human motion analysis.

    Technical contributions of this thesis introduce computer vision-based, marker-less systems to estimate and analyze body motion. The main focus of this research work is on head and hand motion analysis due to the fact that they are the most frequently used body parts for interacting with computers. This thesis gives an insight into the technical challenges and provides new perspectives and robust techniques for solving the problem.

  • 2.
    Abedan Kondori, Farid
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för tillämpad fysik och elektronik.
    Human Motion Analysis for Creating Immersive Experiences2012Licentiatavhandling, sammanläggning (Övrigt vetenskapligt)
    Abstract [en]

    From an early age, people display the ability to quickly and effortlessly interpret the orientation and movement of human body parts, thereby allowing one to infer the intentions of others who are nearby and to comprehend an important nonverbal form of communication. The ease with which one accomplishes this task belies the difficulty of a problem that has challenged computational systems for decades, human motion analysis.

    Technological developments over years have resulted into many systems for measuring body segment positions and angles between segments. In these systems human body is typically considered as a system of rigid links connected by joints. The motion is estimated by the use of measurements from mechanical, optical, magnetic, or inertial trackers. Among all kinds of sensors, optical sensing encompasses a large and varying collection of technologies.

    In a computer vision context, human motion analysis is a topic that studies methods and applications in which two or more consecutive images from an image sequences, e.g. captured by a video camera, are processed to produce information based on the apparent human body motion in the images.

    Many different disciplines employ motion analysis systems to capture movement and posture of human body for applications such as medical diagnostics, virtual reality, human-computer interaction etc.

    This thesis gives an insight into the state of the art human motion analysissystems, and provides new methods for capturing human motion.

  • 3.
    Abedan Kondori, Farid
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för tillämpad fysik och elektronik.
    Liu, Li
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för tillämpad fysik och elektronik.
    3D Active Human Motion Estimation for Biomedical Applications2012Ingår i: World Congress on Medical Physics and Biomedical Engineering May 26-31, 2012, Beijing, China / [ed] Mian Long, Springer Berlin/Heidelberg, 2012, , s. 4s. 1014-1017Konferensbidrag (Refereegranskat)
    Abstract [en]

    Movement disorders forbid many people from enjoying their daily lives. As with other diseases, diagnosis and analysis are key issues in treating such disorders. Computer vision-based motion capture systems are helpful tools for accomplishing this task. However Classical motion tracking systems suffer from several limitations. First they are not cost effective. Second these systems cannot detect minute motions accurately. Finally they are spatially limited to the lab environment where the system is installed. In this project, we propose an innovative solution to solve the above-mentioned issues. Mounting the camera on human body, we build a convenient, low cost motion capture system that can be used by the patient while practicing daily-life activities. We refer to this system as active motion capture, which is not confined to the lab environment. Real-time experiments in our lab revealed the robustness and accuracy of the system.

  • 4.
    Abedan Kondori, Farid
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för tillämpad fysik och elektronik.
    Yousefi, Shahrouz
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för tillämpad fysik och elektronik.
    Smart Baggage in Aviation2011Ingår i: 2011 IEEE International Conferences on Internet of Things, and Cyber, Physical and Social Computing / [ed] Feng Xia, Zhikui Chen, Gang Pan, Laurence T. Yang, and Jianhua Ma, Los Alamitos: IEEE Computer Society, 2011, s. 620-623Konferensbidrag (Refereegranskat)
    Abstract [en]

    Nowadays, the Internet has dramatically changed the way people take the normal course of actions. By the recent growth of the Internet, connecting different objects to users through mobile phones and computers is no longer a dream. Aviation industry is one of the areas which have a strong potential to benefit from the Internet of Things. Among many problems related to air travel, delayed and lost luggage are the most common and irritating. Therefore, this paper suggests anew baggage control system, where users can simply track their baggage at the airport to avoid losing them. Attaching a particular pattern on the bag, which can be detected and localized from long distance by an ordinary camera, users are able to track their baggage. The proposed system is much cheaper than previous implementations and does not require sophisticated equipment.

  • 5.
    Abedan Kondori, Farid
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för tillämpad fysik och elektronik.
    Yousefi, Shahrouz
    KTH Royal Institute of Technology, Department of Media Technology and Interaction Design.
    Kouma, Jean-Paul
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för tillämpad fysik och elektronik.
    Liu, Li
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för tillämpad fysik och elektronik.
    Li, Haibo
    KTH Royal Institute of Technology, Department of Media Technology and Interaction Design.
    Direct hand pose estimation for immersive gestural interaction2015Ingår i: Pattern Recognition Letters, ISSN 0167-8655, E-ISSN 1872-7344, Vol. 66, s. 91-99Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    This paper presents a novel approach for performing intuitive gesture based interaction using depth data acquired by Kinect. The main challenge to enable immersive gestural interaction is dynamic gesture recognition. This problem can be formulated as a combination of two tasks; gesture recognition and gesture pose estimation. Incorporation of fast and robust pose estimation method would lessen the burden to a great extent. In this paper we propose a direct method for real-time hand pose estimation. Based on the range images, a new version of optical flow constraint equation is derived, which can be utilized to directly estimate 3D hand motion without any need of imposing other constraints. Extensive experiments illustrate that the proposed approach performs properly in real-time with high accuracy. As a proof of concept, we demonstrate the system performance in 3D object manipulation On two different setups; desktop computing, and mobile platform. This reveals the system capability to accommodate different interaction procedures. In addition, a user study is conducted to evaluate learnability, user experience and interaction quality in 3D gestural interaction in comparison to 2D touchscreen interaction.

  • 6.
    Abedan Kondori, Farid
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för tillämpad fysik och elektronik.
    Yousefi, Shahrouz
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för tillämpad fysik och elektronik.
    Li, Haibo
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för tillämpad fysik och elektronik.
    Direct three-dimensional head pose estimation from Kinect-type sensors2014Ingår i: Electronics Letters, ISSN 0013-5194, E-ISSN 1350-911X, Vol. 50, nr 4, s. 268-270Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    A direct method for recovering three-dimensional (3D) head motion parameters from a sequence of range images acquired by Kinect sensors is presented. Based on the range images, a new version of the optical flow constraint equation is derived, which can be used to directly estimate 3D motion parameters without any need of imposing other constraints. Since all calculations with the new constraint equation are based on the range images, Z(xyt), the existing techniques and experiences developed and accumulated on the topic of motion from optical flow can be directly applied simply by treating the range images as normal intensity images I(xyt). In this reported work, it is demonstrated how to employ the new optical flow constraint equation to recover the 3D motion of a moving head from the sequences of range images, and furthermore, how to use an old trick to handle the case when the optical flow is large. It is shown, in the end, that the performance of the proposed approach is comparable with that of some of the state-of-the-art approaches that use range data to recover 3D motion parameters.

  • 7.
    Abedan Kondori, Farid
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för tillämpad fysik och elektronik.
    Yousefi, Shahrouz
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för tillämpad fysik och elektronik.
    Li, Haibo
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för tillämpad fysik och elektronik.
    Gesture Tracking for 3D Interaction in Augmented Environments2011Konferensbidrag (Övrigt vetenskapligt)
  • 8.
    Abedan Kondori, Farid
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för tillämpad fysik och elektronik.
    Yousefi, Shahrouz
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för tillämpad fysik och elektronik.
    Li, Haibo
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för tillämpad fysik och elektronik.
    Real 3D Interaction Behind Mobile Phones for Augmented Environments2011Ingår i: 2011 IEEE International Conference on Multimedia and Expo (ICME), IEEE conference proceedings, 2011, s. 1-6Konferensbidrag (Refereegranskat)
    Abstract [en]

    Number of mobile devices such as mobile phones or PDAs has been dramatically increased over the recent years. New mobile devices are equipped with integrated cameras and large displays which make the interaction with device easier and more efficient. Although most of the previous works on interaction between humans and mobile devices are based on 2D touch-screen displays, camera-based interaction opens a new way to manipulate in 3D space behind the device in the camera's field of view. This paper suggests the use of particular patterns from local orientation of the image called Rotational Symmetries to detect and localize human gesture. Relative rotation and translation of human gesture between consecutive frames are estimated by means of extracting stable features. Consequently, this information can be used to facilitate the 3D manipulation of virtual objects in various applications in mobile devices.

  • 9.
    Abedan Kondori, Farid
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för tillämpad fysik och elektronik.
    Yousefi, Shahrouz
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för tillämpad fysik och elektronik.
    Li, Haibo
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för tillämpad fysik och elektronik.
    Sonning, Samuel
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för tillämpad fysik och elektronik.
    Sonning, Sabina
    3D Head Pose Estimation Using the Kinect2011Konferensbidrag (Refereegranskat)
    Abstract [en]

    Head pose estimation plays an essential role for bridging the information gap between humans and computers. Conventional head pose estimation methods are mostly done in images captured by cameras. However accurate and robust pose estimation is often problematic. In this paper we present an algorithm for recovering the six degrees of freedom (DOF) of motion of a head from a sequence of range images taken by the Microsoft Kinectfor Xbox 360. The proposed algorithm utilizes a least-squares minimization of the difference between themeasured rate of change of depth at a point and the rate predicted by the depth rate constraint equation. We segment the human head from its surroundings and background, and then we estimate the head motion. Our system has the capability to recover the six DOF of the head motion of multiple people in one image. Theproposed system is evaluated in our lab and presents superior results.

  • 10.
    Abedan Kondori, Farid
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för tillämpad fysik och elektronik.
    Yousefi, Shahrouz
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för tillämpad fysik och elektronik.
    Liu, Li
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för tillämpad fysik och elektronik.
    Active human gesture capture for diagnosing and treating movement disorders2013Konferensbidrag (Övrigt vetenskapligt)
    Abstract [en]

    Movement disorders prevent many people fromenjoying their daily lives. As with other diseases, diagnosisand analysis are key issues in treating such disorders.Computer vision-based motion capture systems are helpfultools for accomplishing this task. However Classical motiontracking systems suffer from several limitations. First theyare not cost effective. Second these systems cannot detectminute motions accurately. Finally they are spatially limitedto the lab environment where the system is installed. In thisproject, we propose an innovative solution to solve the abovementionedissues. Mounting the camera on human body, webuild a convenient, low cost motion capture system that canbe used by the patient in daily-life activities. We refer tothis system as active motion capture, which is not confinedto the lab environment. Real-time experiments in our labrevealed the robustness and accuracy of the system.

  • 11.
    Abedan Kondori, Farid
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för tillämpad fysik och elektronik.
    Yousefi, Shahrouz
    KTH Royal Institute of Technology, Department of Media Technology and Interaction Design.
    Liu, Li
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för tillämpad fysik och elektronik.
    Li, Haibo
    KTH Royal Institute of Technology, Department of Media Technology and Interaction Design.
    Head operated electric wheelchair2014Ingår i: IEEE Southwest Symposium on Image Analysis and Interpretation (SSIAI 2014), IEEE , 2014, s. 53-56Konferensbidrag (Refereegranskat)
    Abstract [en]

    Currently, the most common way to control an electric wheelchair is to use joystick. However, there are some individuals unable to operate joystick-driven electric wheelchairs due to sever physical disabilities, like quadriplegia patients. This paper proposes a novel head pose estimation method to assist such patients. Head motion parameters are employed to control and drive an electric wheelchair. We introduce a direct method for estimating user head motion, based on a sequence of range images captured by Kinect. In this work, we derive new version of the optical flow constraint equation for range images. We show how the new equation can be used to estimate head motion directly. Experimental results reveal that the proposed system works with high accuracy in real-time. We also show simulation results for navigating the electric wheelchair by recovering user head motion.

  • 12.
    Abedan Kondori, Farid
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för tillämpad fysik och elektronik.
    Yousefi, Shahrouz
    Ostovar, Ahmad
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Liu, Li
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för tillämpad fysik och elektronik.
    Li, Haibo
    A Direct Method for 3D Hand Pose Recovery2014Ingår i: 22nd International Conference on Pattern Recognition, 2014, s. 345-350Konferensbidrag (Refereegranskat)
    Abstract [en]

    This paper presents a novel approach for performing intuitive 3D gesture-based interaction using depth data acquired by Kinect. Unlike current depth-based systems that focus only on classical gesture recognition problem, we also consider 3D gesture pose estimation for creating immersive gestural interaction. In this paper, we formulate gesture-based interaction system as a combination of two separate problems, gesture recognition and gesture pose estimation. We focus on the second problem and propose a direct method for recovering hand motion parameters. Based on the range images, a new version of optical flow constraint equation is derived, which can be utilized to directly estimate 3D hand motion without any need of imposing other constraints. Our experiments illustrate that the proposed approach performs properly in real-time with high accuracy. As a proof of concept, we demonstrate the system performance in 3D object manipulation. This application is intended to explore the system capabilities in real-time biomedical applications. Eventually, system usability test is conducted to evaluate the learnability, user experience and interaction quality in 3D interaction in comparison to 2D touch-screen interaction.

  • 13.
    Kondori, Farid Abedan
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för tillämpad fysik och elektronik.
    Liu, Li
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för tillämpad fysik och elektronik.
    Li, Haibo
    KTH Royal Institue of Technology, Department of Media Technology and Interaction Design, School of Computer Science and Communication.
    Telelife: An immersive media experience for rehabilitation2014Ingår i: Proceedings of the 2014 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA 2014), IEEE, 2014Konferensbidrag (Refereegranskat)
    Abstract [en]

    In recent years, emergence of telerehabilitation systems for home-based therapy has altered healthcare systems. Telerehabilitation enables therapists to observe patients status via Internet, thus a patient does not have to visit rehabilitation facilities for every rehabilitation session. Despite the fact that telerehabilitation provides great opportunities, there are two major issues that affect effectiveness of telerehabilitation: relegation of the patient at home, and loss of direct supervision of the therapist. Since patients have no actual interaction with other persons during the rehabilitation period, they will become isolated and gradually lose their social skills. Moreover, without direct supervision of therapists, rehabilitation exercises can be performed with bad compensation strategies that lead to a poor quality recovery. To resolve these issues, we propose telelife, a new concept for future rehabilitation systems. The idea is to use media technology to create a totally new immersive media experience for rehabilitation. In telerehabilitation patients locally execute exercises, and therapists remotely monitor patients' status. In telelife patients, however, remotely perform exercises and therapists locally monitor. Thus, not only telelife enables rehabilitation at distance, but also improves the patients' social competences, and provides direct supervision of therapists. In this paper we introduce telelife to enhance telerehabilitation, and investigate technical challenges and possible methods to achieve telelife.

  • 14.
    Yousefi, Shahrouz
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för tillämpad fysik och elektronik.
    Abedan Kondori, Farid
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för tillämpad fysik och elektronik.
    Li, Haibo
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för tillämpad fysik och elektronik.
    Tracking fingers in 3D space for mobile interaction2010Konferensbidrag (Refereegranskat)
    Abstract [en]

    Number of mobile devices such as mobile phones or PDAs has been dramatically increased over the recent years. New mobile devices are equipped with integrated cameras and large displays which make the interaction with device easier and more efficient. Although most of the previous works on interaction between humans and mobile devices are based on 2D touch-screen displays, camera-based interaction opens a new way to manipulate in 3D space behind the device in the camera's field of view.In this paper, our gestural interaction relies heavily on particular patterns from local orientation of the image called Rotational Symmetries. This approach is based on finding the most suitable pattern from the large set of rotational symmetries of different orders which ensures a reliable detector for fingertips and human gesture. Consequently, gesture detection and tracking can be used as an efficient tool for 3D manipulation in various applications in computer vision and augmented reality.

  • 15.
    Yousefi, Shahrouz
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för tillämpad fysik och elektronik.
    Kondori, Farid Abedan
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för tillämpad fysik och elektronik.
    Li, Haibo
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för tillämpad fysik och elektronik.
    3D Gestural Interaction for Stereoscopic Visualization on Mobile Devices2011Ingår i: Computer Analysis of Images and Patterns: 14th International Conference, CAIP 2011, PT 2 / [ed] Real, P; DiazPernil, D; MolinaAbril, H; Berciano, A; Kropatsch, W, Berlin: Springer Berlin/Heidelberg, 2011, s. 555-562Konferensbidrag (Refereegranskat)
    Abstract [en]

    Number of mobile devices such as smart phones or Tablet PCs has been dramatically increased over the recent years. New mobile devices are equipped with integrated cameras and large displays which make the interaction with device more efficient. Although most of the previous works on interaction between humans and mobile devices are based on 2D touch-screen displays, camera-based interaction opens a new way to manipulate in 3D space behind the device in the camera's field of view. In this paper, our gestural interaction heavily relies on particular patterns from local orientation of the image called Rotational Symmetries. This approach is based on finding the most suitable pattern from a large set of rotational symmetries of different orders which ensures a reliable detector for hand gesture. Consequently, gesture detection and tracking can be hired as an efficient tool for 3D manipulation in various applications in computer vision and augmented reality. The final output will be rendered into color anaglyphs for 3D visualization. Depending on the coding technology different low cost 3D glasses will be used for viewers.

  • 16.
    Yousefi, Shahrouz
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för tillämpad fysik och elektronik.
    Kondori, Farid Abedan
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för tillämpad fysik och elektronik.
    Li, Haibo
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för tillämpad fysik och elektronik.
    3D Visualization of Monocular Images in Photo Collections2011Konferensbidrag (Refereegranskat)
  • 17.
    Yousefi, Shahrouz
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för tillämpad fysik och elektronik.
    Kondori, Farid Abedan
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för tillämpad fysik och elektronik.
    Li, Haibo
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för tillämpad fysik och elektronik.
    3D visualization of single images using patch level depth2011Ingår i: 2011 PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING AND MULTIMEDIA APPLICATIONS (SIGMAP 2011) / [ed] Barranco, AL & Tsihrintzis, G, IEEE, 2011, s. 1-6Konferensbidrag (Refereegranskat)
    Abstract [en]

    In this paper we consider the task of 3D photo visualization using a single monocular image. The main idea is to use single photos taken by capturing devices such as ordinary cameras, mobile phones, tablet PCs etc. and visualize them in 3D on normal displays. Supervised learning approach is hired to retrieve depth information from single images. This algorithm is based on the hierarchical multi-scale Markov Random Field (MRF) which models the depth based on the multi-scale global and local features and relation between them in a monocular image. Consequently, the estimated depth image is used to allocate the specified depth parameters for each pixel in the 3D map. Accordingly, the multi-level depth adjustments and coding for color anaglyphs is performed. Our system receives a single 2D image as input and provides a anaglyph coded 3D image in output. Depending on the coding technology the special low-cost anaglyph glasses for viewers will be used.

  • 18.
    Yousefi, Shahrouz
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för tillämpad fysik och elektronik.
    Kondori, Farid Abedan
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för tillämpad fysik och elektronik.
    Li, Haibo
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för tillämpad fysik och elektronik.
    Camera-based gesture tracking for 3D interaction behind mobile devices2012Ingår i: International journal of pattern recognition and artificial intelligence, ISSN 0218-0014, Vol. 26, nr 8, s. 1260008-Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Number of mobile devices such as Smartphones or Tablet PCs has been dramatically increased over the recent years. New mobile devices are equipped with integrated cameras and large displays that make the interaction with the device easier and more efficient. Although most of the previous works on interaction between humans and mobile devices are based on 2D touch-screen displays, camera-based interaction opens a new way to manipulate in 3D space behind the device in the camera's field of view. In this paper, our gestural interaction relies on particular patterns from local orientation of the image called rotational symmetries. This approach is based on finding the most suitable pattern from a large set of rotational symmetries of diffrerent orders that ensures a reliable detector for fingertips and user's gesture. Consequently, gesture detection and tracking can be used as an efficient tool for 3D manipulation in various virtual/augmented reality applications.

  • 19.
    Yousefi, Shahrouz
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för tillämpad fysik och elektronik.
    Kondori, Farid Abedan
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för tillämpad fysik och elektronik.
    Li, Haibo
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för tillämpad fysik och elektronik.
    Experiencing real 3D gestural interaction with mobile devices2013Ingår i: Pattern Recognition Letters, ISSN 0167-8655, E-ISSN 1872-7344, Vol. 34, nr 8, s. 912-921Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Number of mobile devices such as smart phones or Tablet PCs has been dramatically increased over the recent years. New mobile devices are equipped with integrated cameras and large displays which make the interaction with the device more efficient. Although most of the previous works on interaction between humans and mobile devices are based on 2D touch-screen displays, camera-based interaction opens a new way to manipulate in 3D space behind the device, in the camera's field of view. In this paper, our gestural interaction heavily relies on particular patterns from local orientation of the image called Rotational Symmetries. This approach is based on finding the most suitable pattern from a large set of rotational symmetries of different orders that ensures a reliable detector for hand gesture. Consequently, gesture detection and tracking can be hired as an efficient tool for 3D manipulation in various applications in computer vision and augmented reality. The final output will be rendered into color anaglyphs for 3D visualization. Depending on the coding technology, different low cost 3D glasses can be used for the viewers. (C) 2013 Elsevier B.V. All rights reserved.

  • 20. Yousefi, Shahrouz
    et al.
    Kondori, Farid Abedan
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för tillämpad fysik och elektronik.
    Li, Haibo
    Interactive 3D visualization on a 4K wall-sized display2014Ingår i: Proceedings of 2014 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA 2014), IEEE, 2014Konferensbidrag (Refereegranskat)
    Abstract [en]

    This paper introduces a novel vision-based approach for realistic interaction between user and display's content. An extremely accurate motion capture system is proposed to measure and track the user's head motion in 3D space. Video frames captured by the low-cost head-mounted camera are processed to retrieve the 3D motion parameters. The retrieved information facilitates the real-time 3D interaction. This technology turns any 2D screen to interactive 3D display, enabling users to control and manipulate the content as a digital window. The proposed system is tested and verified on a huge wall-sized 4K screen.

  • 21.
    Yousefi, Shahrouz
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för tillämpad fysik och elektronik.
    Kondori, Farid Abedan
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för tillämpad fysik och elektronik.
    Li, Haibo
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för tillämpad fysik och elektronik.
    Robust correction of 3D geo-metadata in photo collections by forming a photo grid2011Ingår i: 2011 International Conference on Wireless Communications and Signal Processing (WCSP), IEEE, 2011, s. 1-5Konferensbidrag (Refereegranskat)
    Abstract [en]

    In this work, we present a technique for efficient and robust estimation of the exact location and orientation of a photo capture device in a large data set. The provided data set includes a set of photos and the associated information from GPS and orientation sensor. This attached metadata is noisy and lacks precision. Our strategy to correct this uncertain data is based on the data fusion between measurement model, derived from sensor data, and signal model given by the computer vision algorithms. Based on the retrieved information from multiple views of a scene we make a grid of images. Our robust feature detection and matching between images result in finding a reliable transformation. Consequently, relative location and orientation of the data set construct the signal model. On the other hand, information extracted from the single images combined with the measurement data make the measurement model. Finally, Kalman filter is used to fuse these two models iteratively and enhance the estimation of the ground truth(GT) location and orientation. Practically, this approach can help us to design a photo browsing system from a huge collection of photos, enabling 3D navigation and exploration of our huge data set.

  • 22.
    Yousefi, Shahrouz
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för tillämpad fysik och elektronik.
    Kondori, Farid Abedan
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för tillämpad fysik och elektronik.
    Li, Haibo
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för tillämpad fysik och elektronik.
    Stereoscopic visualization of monocular images in photo collections2011Konferensbidrag (Refereegranskat)
1 - 22 av 22
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