| 1. |
- Yousefi, Shahrouz, et al.
(författare)
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3D Gestural Interaction for Stereoscopic Visualization on Mobile Devices
- 2011
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Ingår i: Computer Analysis of Images and Patterns. - Berlin : Springer. - 9783642236778 ; , s. 555-562, s. 555-562
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Konferensbidrag (refereegranskat)abstract
- 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.
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| 2. |
- Abedan Kondori, Farid, 1983-, et al.
(författare)
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3D Active Human Motion Estimation for Biomedical Applications
- 2012
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Ingår i: World Congress on Medical Physics and Biomedical Engineering May 26-31, 2012, Beijing, China. - Berlin, Heidelberg : Springer Berlin/Heidelberg. - 9783642293047 - 9783642293054 ; , s. 1014-1017
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Konferensbidrag (refereegranskat)abstract
- 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.
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| 3. |
- Abedan Kondori, Farid, et al.
(författare)
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3D head pose estimation using the Kinect
- 2011
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Ingår i: 2011 International Conference on Wireless Communications and Signal Processing (WCSP). - : IEEE Press. ; , s. 1-4
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Konferensbidrag (refereegranskat)abstract
- 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 Kinect for Xbox 360. The proposed algorithm utilizes a least-squares minimization of the difference between the measured 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. The proposed system is evaluated in our lab and presents superior results.
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| 4. |
- Abedan Kondori, Farid, et al.
(författare)
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A Direct Method for 3D Hand Pose Recovery
- 2014
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Ingår i: 2014 22ND INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION (ICPR). - : IEEE COMPUTER SOC. - 9781479952083 ; , s. 345-350
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Konferensbidrag (refereegranskat)abstract
- 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.
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| 5. |
- Abedan Kondori, Farid, 1983-, et al.
(författare)
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Active human gesture capture for diagnosing and treating movement disorders
- 2013
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Ingår i: Proceeding of The Swedish Symposium on Image Analysis (SSBA2013), Gothenburg, Sweden.
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- 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.
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| 6. |
- Abedan Kondori, Farid, 1983-
(författare)
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Bring Your Body into Action : Body Gesture Detection, Tracking, and Analysis for Natural Interaction
- 2014
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- 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.
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| 7. |
- Abedan Kondori, Farid, 1983-, et al.
(författare)
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Direct hand pose estimation for immersive gestural interaction
- 2015
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Ingår i: Pattern Recognition Letters. - : Elsevier BV. - 0167-8655 .- 1872-7344. ; 66, s. 91-99
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Tidskriftsartikel (refereegranskat)abstract
- 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.
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| 8. |
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| 9. |
- Abedan Kondori, Farid, 1983-, et al.
(författare)
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Direct three-dimensional head pose estimation from Kinect-type sensors
- 2014
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Ingår i: Electronics Letters. - : Institution of Engineering and Technology (IET). - 0013-5194 .- 1350-911X. ; 50:4, s. 268-270
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Tidskriftsartikel (refereegranskat)abstract
- 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(x, y, t), 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(x, y, t). 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.
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| 10. |
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