Browsing by Author "Lai, Yu-Chun"

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A Local Feature-based Human Motion Recognition Framework
(2009)
Lai, Yu-Chun
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Liao, Hong-Yuan Mark
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Lin, Cheng-Chung
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Chen, Jian-Ren
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Luo, Y. -F. Peter
In this paper, we propose a local feature-based human motion analysis framework Instead of using traditional analysis methods to characterize the global structure of human motion, we extract features directly from local regions that contain motion. To implement the above concept, we adopt the rules of visual attention theory, which assert that a human motion can be described simply by a set of local features comprised of spatial relationships rather than human postures. We select two kinds of features to represent the local variation of a human motion. First, we extract the long-term movement trend of the motion. The second feature is actually a set of rough features derived by sampling multi-scale moving edges. The two types of features are considered together during the recognition process. Our experiments demonstrate that the proposed approach can achieve very good recognition results.
Human motion recognition using clay representation of trajectories
(2006)
Lai, Yu-Chun
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Liao, Hong-Yuan Mark
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資訊工程學系
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Department of Computer Science
In this paper, we propose a novel human motion recognition approach that incorporates two fundamental concepts. First, the Shape Context and a clustering method are used to extract moving articulated parts from a video sequence. Then, we represent the moving articulated parts by trajectories. Our trajectory extraction approach provides good tolerance under various background and lighting conditions. Significantly, landmark point selection is not necessary in our approach, since trajectory generation is based on the extraction of moving articulated parts. The second concept is that the extracted trajectories are seen as forces pushing the articulated parts. Those forces are applied to a claylike deformed material, which is used to represent the trajectories' behavior. The experiment results show that the proposed approach is robust against noise and incorrectly extracted trajectories, such as redundant and missing trajectories.
LINEAR PRODUCTION GAME SOLUTION TO A PTZ CAMERA NETWORK
(2010)
Lai, Yu-Chun
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Liang, Yu-Ming
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Shih, Sheng-Wen
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Liao, Hong-Yuan Mark
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Lin, Cheng-Chung
Reconfiguring the PTZ parameters of a camera network is an combinatorial optimization problem and computing the optimal solution is very time consuming. Therefore, existing methods can only provide sub-optimal solutions. In this paper, a nonlinear objective function for better utilizing the cameras to track multiple targets is proposed. Furthermore, it is shown that by expanding the unknown parameters and imposing new constraints, the nonlinear objective function can be converted into a linear production game (LPG) problem. Since an LPG possesses an optimal solution which can be evaluated with polynomial time, the proposed method is efficient and accurate. Computer simulations have been conducted and the results show that the proposed method is very promising.
Linear Production Game Solution to a PTZ Camera Network
(2013-05-01)
Lai, Yu-Chun
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Liang, Yu-Ming
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Shih, Sheng-Wen
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Lin, Cheng-Chung
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Liao, Hong-Yuan Mark
Reconfiguring the parameters of PTZ cameras in a surveillance system is a combinatorial optimization problem. Computing the optimal solution is very time consuming, and existing methods can only provide sub-optimal solutions. In this paper, we propose a non-linear objective function that better utilizes a camera network to track multiple targets. We also show that, by expanding the unknown parameters and imposing new constraints, the non-linear objective function can be converted into a linear production game (LPG) problem. Since an LPG yields an optimal solution that can be evaluated in polynomial time, the proposed method is efficient and accurate. The results of simulations and a real-world experiment demonstrate the proposed method's potential.
Movie scene segmentation using background information
(2008-03-01)
Chen, Liang-Hua
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Lai, Yu-Chun
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Liao, Hong-Yuan Mark
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資訊工程學系
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Department of Computer Science
Scene extraction is the first step toward semantic understanding of a video. It also provides improved browsing and retrieval facilities to users of video database. This paper presents an effective approach to movie scene extraction based on the analysis of background images. Our approach exploits the fact that shots belonging to one particular scene often have similar backgrounds. Although part of the video frame is covered by foreground objects, the background scene can still be reconstructed by a mosaic technique. The proposed scene extraction algorithm consists of two main components: determination of the shot similarity measure and a shot grouping process. In our approach, several low-level visual features are integrated to compute the similarity measure between two shots. On the other hand, the rules of film-making are used to guide the shot grouping process. Experimental results show that our approach is promising and outperforms some existing techniques. (C) 2007 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.
Segmentation of human body parts in video frames based on intrinsic distance
(2007)
Lai, Yu-Chun
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Liao, Hong-Yuan Mark
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Lin, Cheng-Chung
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資訊工程學系
;
Department of Computer Science
We propose an intrinsic-distance based segmentation approach for segmenting human body parts in video frames. First, since the human body can be seen as a set of articulated parts, we utilize the moving articulated attributes to identify body part candidate regions automatically. The candidate regions and the background candidate regions are generated by voting and assigned to the spatiotemporal volume, which is comprised of frames of the video. Then, the intrinsic distance is used to estimate the boundaries of each body part. Our intrinsic distance-based segmentation technique is applied in the spatiotemporal volume to extract the optimal boundaries of the intrinsic distance in a video and obtain segmented frames from the segmented volume. The segmented results show that the proposed approach can tolerate incomplete and imprecise candidate regions because it provides temporal continuity. Furthermore, it can reduce over growing in the original intrinsic distance-based algorithm, since it can handle ambiguous pixels. We expect that this research can provide an alternative to segmenting a sequence of body parts in a video.
Video scene extraction using mosaic technique
(2006)
Chen, Liang-Hua
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Lai, Yu-Chun
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Liao, Hong-Yuan
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資訊工程學系
;
Department of Computer Science
Scene extraction is the first step toward semantic understanding of the video. This paper presents an effective approach to video scene extraction based on the analysis of background images. Our approach exploits the fact that shots belonging to one particular scene often have similar background. Although part of the video frame is covered by foreground objects, background scene still can be reconstructed by mosaic technique. The proposed scene extraction algorithm consists of two main components: the determination of shot similarity measure and shot grouping process. In our approach, several low-level visual features are integrated to compute the similarity measure between two shots. On the other hand, high-level knowledge in cinematography is used to guide the shot grouping process. Experimental results show that our approach is promising and outperforms some existing technique.