Measuring the Effects of Occlusion on Kernel Based Object Tracking Using Simulated Videos

Occlusion handling is one of the most studied problems for object tracking in computer vision. Many previous works claimed that occlusion can be handled effectively using Kalman filter, Particle filter and Mean Shift tracking methods. However, these methods were only tested on specific task videos...

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主要な著者: Beng, Yong Lee, Lee, Hung Liew, WaiShiang, Cheah, Yin, Chai Wang
フォーマット: 論文
言語:English
出版事項: Elsevier 2012
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オンライン・アクセス:http://ir.unimas.my/id/eprint/17380/1/Measuring%20the%20Effects%20of%20Occlusion%20on%20Kernel%20Based%20Object%20Tracking%20%28abstract%29.pdf
http://ir.unimas.my/id/eprint/17380/
http://www.sciencedirect.com/science/article/pii/S1877705812026410
https://doi.org/10.1016/j.proeng.2012.07.241
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spelling my.unimas.ir.173802022-09-29T08:04:13Z http://ir.unimas.my/id/eprint/17380/ Measuring the Effects of Occlusion on Kernel Based Object Tracking Using Simulated Videos Beng, Yong Lee Lee, Hung Liew WaiShiang, Cheah Yin, Chai Wang T Technology (General) Occlusion handling is one of the most studied problems for object tracking in computer vision. Many previous works claimed that occlusion can be handled effectively using Kalman filter, Particle filter and Mean Shift tracking methods. However, these methods were only tested on specific task videos. In order to explore the actual potential of these methods, this paper examined the tracking methods with six simulation videos that consider various occlusion scenarios. Tracking performances are evaluated based on Sequence Frame Detection Accuracy (SFDA). The results show that Mean shift tracker would fail completely when full occlusion occurs as claimed by many previous works. In most cases, Kalman filter and Particle filter tracker achieved SFDA score between 0.3 and 0.4. It demonstrates that Particle filter tracker fails to detect object with arbitrary movement in one of the experiments. The effect of occlusion on each tracker is analysed with Frame Detection Accuracy (FDA) graph. Elsevier 2012 Article PeerReviewed text en http://ir.unimas.my/id/eprint/17380/1/Measuring%20the%20Effects%20of%20Occlusion%20on%20Kernel%20Based%20Object%20Tracking%20%28abstract%29.pdf Beng, Yong Lee and Lee, Hung Liew and WaiShiang, Cheah and Yin, Chai Wang (2012) Measuring the Effects of Occlusion on Kernel Based Object Tracking Using Simulated Videos. Procedia Engineering, 41. pp. 764-770. ISSN 1877-7058 http://www.sciencedirect.com/science/article/pii/S1877705812026410 https://doi.org/10.1016/j.proeng.2012.07.241
institution Universiti Malaysia Sarawak
building Centre for Academic Information Services (CAIS)
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Sarawak
content_source UNIMAS Institutional Repository
url_provider http://ir.unimas.my/
language English
topic T Technology (General)
spellingShingle T Technology (General)
Beng, Yong Lee
Lee, Hung Liew
WaiShiang, Cheah
Yin, Chai Wang
Measuring the Effects of Occlusion on Kernel Based Object Tracking Using Simulated Videos
description Occlusion handling is one of the most studied problems for object tracking in computer vision. Many previous works claimed that occlusion can be handled effectively using Kalman filter, Particle filter and Mean Shift tracking methods. However, these methods were only tested on specific task videos. In order to explore the actual potential of these methods, this paper examined the tracking methods with six simulation videos that consider various occlusion scenarios. Tracking performances are evaluated based on Sequence Frame Detection Accuracy (SFDA). The results show that Mean shift tracker would fail completely when full occlusion occurs as claimed by many previous works. In most cases, Kalman filter and Particle filter tracker achieved SFDA score between 0.3 and 0.4. It demonstrates that Particle filter tracker fails to detect object with arbitrary movement in one of the experiments. The effect of occlusion on each tracker is analysed with Frame Detection Accuracy (FDA) graph.
format Article
author Beng, Yong Lee
Lee, Hung Liew
WaiShiang, Cheah
Yin, Chai Wang
author_facet Beng, Yong Lee
Lee, Hung Liew
WaiShiang, Cheah
Yin, Chai Wang
author_sort Beng, Yong Lee
title Measuring the Effects of Occlusion on Kernel Based Object Tracking Using Simulated Videos
title_short Measuring the Effects of Occlusion on Kernel Based Object Tracking Using Simulated Videos
title_full Measuring the Effects of Occlusion on Kernel Based Object Tracking Using Simulated Videos
title_fullStr Measuring the Effects of Occlusion on Kernel Based Object Tracking Using Simulated Videos
title_full_unstemmed Measuring the Effects of Occlusion on Kernel Based Object Tracking Using Simulated Videos
title_sort measuring the effects of occlusion on kernel based object tracking using simulated videos
publisher Elsevier
publishDate 2012
url http://ir.unimas.my/id/eprint/17380/1/Measuring%20the%20Effects%20of%20Occlusion%20on%20Kernel%20Based%20Object%20Tracking%20%28abstract%29.pdf
http://ir.unimas.my/id/eprint/17380/
http://www.sciencedirect.com/science/article/pii/S1877705812026410
https://doi.org/10.1016/j.proeng.2012.07.241
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score 13.250246