標題: | MOVING TARGETS LABELING AND CORRESPONDENCE OVER MULTI-CAMERA SURVEILLANCE SYSTEM BASED ON MARKOV NETWORK |
作者: | Huang, Ching-Chun Wang, Sheng-Jyh 電子工程學系及電子研究所 Department of Electronics Engineering and Institute of Electronics |
關鍵字: | Image labeling;Object correspondence;Markov Chain Monte Carlo;Mean-Shift;Graphical models |
公開日期: | 2009 |
摘要: | In this paper, we propose an efficient way to simultaneously label and map targets over a multi-camera surveillance system. In the system, we first fuse the detection results from multiple cameras into a posterior distribution. This distribution indicates the likelihood of having some moving targets on the ground plane. Based on the distribution, isolated targets, together with their 3-D positions, are identified in a sample-based manner, which combines Markov Chain Monte Carlo (MCMC), and Mean-Shift clustering. The induced 3-D scene information is further inputted into a 3-layer Bayesian hierarchical framework (BHF), which adopts a Markov network to deal with the object labeling and correspondence problems. In principle, labeling and correspondence are regarded as a unified optimal problem subject to 3-D scene prior, image color similarity, and detection results. The experiments show that accurate results can be gotten even under situations with severe occlusion. |
URI: | http://hdl.handle.net/11536/16258 |
ISBN: | 978-1-4244-4290-4 |
ISSN: | 1945-7871 |
期刊: | ICME: 2009 IEEE INTERNATIONAL CONFERENCE ON MULTIMEDIA AND EXPO, VOLS 1-3 |
起始頁: | 1258 |
結束頁: | 1261 |
顯示於類別: | 會議論文 |