The Experts below are selected from a list of 15936 Experts worldwide ranked by ideXlab platform
Deokhwa Hong - One of the best experts on this subject based on the ideXlab platform.
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IROS - Microassembly using a variable view imaging system to overcome small FOV and Occlusion Problems
2010 IEEE RSJ International Conference on Intelligent Robots and Systems, 2010Co-Authors: Xiaodong Tao, Hyungsuck Cho, Deokhwa HongAbstract:In this paper, the variable view imaging system (VVIS) developed to offer flexibility in microscopic observation is applied to microassembly tasks to overcome several Problems in normal imaging systems that hindered application of vision-guided micromanipulation techniques such as limited field of view (FOV) and fixed viewing direction. In three representative cases of microassembly, the parts are mated by visual servoing, avoiding FOV Problem by combining unit FOV's and Occlusion Problem by changing the viewing direction to the optimal one. The results demonstrate the superiority and usefulness of the VVIS in various micromanipulation tasks.
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View planning for occluded region with active imaging system
ICCAS 2010, 2010Co-Authors: Deokhwa HongAbstract:Nowadays, a number of 3D shape measurement methods have been developed such as stereo vision, laser structured light, and Phase Measuring Profilometry (PMP). They have many Problems such as correspondence Problem, 2π-ambiguity and Occlusion Problem. Among them, Occlusion Problem is common Problem for 3D shape measurement and well known as difficult to solve. To solve this Problem, in our previous research, active imaging system is introduced, which can change the viewing angle without changing of field-of-view (FOV), and can do the FOV with maintaining the viewing angle. And to decide the viewing direction and position, view planning algorithm is developed. The performance of our system is checked by simulation and a series of real experiments.
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3D shape measurement in occluded environments based on stereo PMP algorithm
Optomechatronic Technologies 2008, 2008Co-Authors: Hyunki Lee, Deokhwa Hong, Hyungsuck ChoAbstract:Nowadays, a number of 3D measurement methods have been developed such as stereo vision, laser structured light and PMP (Phase Measuring Profilometry) method. However, they have its own limitations : 2π ambiguity, correspondence Problem, long estimation time. To solve these Problems, in our previous researches [9,13], we introduced a novel sensing method adopting stereo vision and PMP technique (stereo PMP algorithm). One other difficult Problem is Occlusion Problem needed to tackle by the stereo PMP algorithm which uses the principle of stereo vision and two cameras. The Occlusion Problem cannot be solved by using the principle of typical stereo vision, because there is no correspondence point in Occlusion area. In our previous research based on stereo PMP algorithm, however, phase information related to the projector's position is additionally used which gives more additional information. By using this additional information, we can solve the Occlusion Problem effectively. In order to detect Occlusion area, we adopt the principle of Dynamic Programming, while to measure the depth the principle of typical PMP algorithm and the geometrical relationship of detected depth area. To verify the efficiency of the proposed method, a series of experimental tests were performed.
Yude Xiong - One of the best experts on this subject based on the ideXlab platform.
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a method for tracking vehicles under Occlusion Problem
International Conference on Image and Graphics, 2015Co-Authors: Cuihong Xue, Luzhen Lian, Yude XiongAbstract:A method of overcoming Occlusion in vehicle tracking system is presented here. Firstly, the features of moving vehicles are extracted by the vehicle detection method which combines background subtraction and bidirectional difference multiplication algorithm. Then, the affection of vehicle cast shadow is reduced by the tail lights detection. Finally, a two-level framework is proposed to handle the vehicle Occlusion which are NP level (No or Partial level) and SF level (Serious or Full level). On the NP level, the vehicles are tracked by mean shift algorithm. On the SF level, Occlusion masks are adaptively created, and the occluded vehicles are tracked in both the original images and the Occlusion masks by utilizing the Occlusion reasoning model. The proposed NP level and SF level are sequentially implemented in this system. The experimental results show that this method can effectively deal with tracking vehicles under ambient Occlusion.
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ICIG (1) - A Method for Tracking Vehicles Under Occlusion Problem
Lecture Notes in Computer Science, 2015Co-Authors: Cuihong Xue, Luzhen Lian, Yude XiongAbstract:A method of overcoming Occlusion in vehicle tracking system is presented here. Firstly, the features of moving vehicles are extracted by the vehicle detection method which combines background subtraction and bidirectional difference multiplication algorithm. Then, the affection of vehicle cast shadow is reduced by the tail lights detection. Finally, a two-level framework is proposed to handle the vehicle Occlusion which are NP level (No or Partial level) and SF level (Serious or Full level). On the NP level, the vehicles are tracked by mean shift algorithm. On the SF level, Occlusion masks are adaptively created, and the occluded vehicles are tracked in both the original images and the Occlusion masks by utilizing the Occlusion reasoning model. The proposed NP level and SF level are sequentially implemented in this system. The experimental results show that this method can effectively deal with tracking vehicles under ambient Occlusion.
Yi Bin Lu - One of the best experts on this subject based on the ideXlab platform.
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Real Time Recogniton and Tracking System of Multiple Vehicles
2006 IEEE Intelligent Vehicles Symposium, 2006Co-Authors: Chung Cheng Chiu, Chun-yi Wang, Min-yu Ku, Yi Bin LuAbstract:This paper proposed a real-time system to recognize and track multiple vehicles. The Occlusion Problem is solved by the Occlusion segmentation method and then each vehicle is recognized according to their outlines and tracked by a tracking algorithm. The proposed recognition method uses the visual length, visual width, roof, windshield, and hood of vehicles to classify the vehicles to vans, utility vehicles, sedans, mini trucks, or large vehicles. Experiments obtained by using complex road scenes are reported, which demonstrate the validity of the method in terms of robustness, accuracy, and time responses
Ming-jing Zhang - One of the best experts on this subject based on the ideXlab platform.
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ICIG (3) - The Research of Long Time Occlusion Problem Based on Object Permanence
Lecture Notes in Computer Science, 2015Co-Authors: Xiang-dan Hou, Ming-jing ZhangAbstract:In the video surveillance system, due to the complicated background, the targets in the movement process often appear some or full of Occlusion. How to detect Occlusions, handle of issues efficiently, especially in the event of long time Occlusion. Accurate target identification and tracking is the key indicators to evaluate the robustness of a target tracking algorithm. This paper deals with long time Occlusions based on the concept of “object permanence” in psychology. This paper proposes a method based on “object permanence” algorithm to solve the identification and tracking Problems after long time Occlusions. The experimental results show that this algorithm can effectively solve the Occlusion Problem.
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the research of long time Occlusion Problem based on object permanence
International Conference on Image and Graphics, 2015Co-Authors: Xiang-dan Hou, Ming-jing ZhangAbstract:In the video surveillance system, due to the complicated background, the targets in the movement process often appear some or full of Occlusion. How to detect Occlusions, handle of issues efficiently, especially in the event of long time Occlusion. Accurate target identification and tracking is the key indicators to evaluate the robustness of a target tracking algorithm. This paper deals with long time Occlusions based on the concept of “object permanence” in psychology. This paper proposes a method based on “object permanence” algorithm to solve the identification and tracking Problems after long time Occlusions. The experimental results show that this algorithm can effectively solve the Occlusion Problem.
Cuihong Xue - One of the best experts on this subject based on the ideXlab platform.
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a method for tracking vehicles under Occlusion Problem
International Conference on Image and Graphics, 2015Co-Authors: Cuihong Xue, Luzhen Lian, Yude XiongAbstract:A method of overcoming Occlusion in vehicle tracking system is presented here. Firstly, the features of moving vehicles are extracted by the vehicle detection method which combines background subtraction and bidirectional difference multiplication algorithm. Then, the affection of vehicle cast shadow is reduced by the tail lights detection. Finally, a two-level framework is proposed to handle the vehicle Occlusion which are NP level (No or Partial level) and SF level (Serious or Full level). On the NP level, the vehicles are tracked by mean shift algorithm. On the SF level, Occlusion masks are adaptively created, and the occluded vehicles are tracked in both the original images and the Occlusion masks by utilizing the Occlusion reasoning model. The proposed NP level and SF level are sequentially implemented in this system. The experimental results show that this method can effectively deal with tracking vehicles under ambient Occlusion.
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ICIG (1) - A Method for Tracking Vehicles Under Occlusion Problem
Lecture Notes in Computer Science, 2015Co-Authors: Cuihong Xue, Luzhen Lian, Yude XiongAbstract:A method of overcoming Occlusion in vehicle tracking system is presented here. Firstly, the features of moving vehicles are extracted by the vehicle detection method which combines background subtraction and bidirectional difference multiplication algorithm. Then, the affection of vehicle cast shadow is reduced by the tail lights detection. Finally, a two-level framework is proposed to handle the vehicle Occlusion which are NP level (No or Partial level) and SF level (Serious or Full level). On the NP level, the vehicles are tracked by mean shift algorithm. On the SF level, Occlusion masks are adaptively created, and the occluded vehicles are tracked in both the original images and the Occlusion masks by utilizing the Occlusion reasoning model. The proposed NP level and SF level are sequentially implemented in this system. The experimental results show that this method can effectively deal with tracking vehicles under ambient Occlusion.
