| 1. |
- Yousefi, Shahrouz, 1983-, et al.
(författare)
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Tracking fingers in 3D space for mobile interaction
- 2010
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Ingår i: The Second International Workshop on Mobile Multimedia Processing (WMMP 2010) in conjunction with The 20th International Conference on Pattern Recognition (ICPR 2010). - : Citeseer. ; , s. 72-79
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Konferensbidrag (refereegranskat)abstract
- 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.
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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, 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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| 4. |
- 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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| 5. |
- 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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| 6. |
- 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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| 7. |
- Abedan Kondori, Farid, 1983-, et al.
(författare)
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Head Operated Electric Wheelchair
- 2014
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Ingår i: Proceedings of the IEEE Southwest Symposium on Image Analysis and Interpretation. - : IEEE Press. - 9781479940530 ; , s. 53-56
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Konferensbidrag (refereegranskat)abstract
- 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.
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| 8. |
- Abedan Kondori, Farid, 1983-
(författare)
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Human Motion Analysis for Creating Immersive Experiences
- 2012
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- 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.
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