會議論文
| 學年 | 97 |
|---|---|
| 學期 | 2 |
| 發表日期 | 2009-03-26 |
| 作品名稱 | Real-time Dynamic Background Segmentation Based on a Statistical Approach |
| 作品名稱（其他語言） | |
| 著者 | Peng, Jian-wen; Horng, Wen-bing |
| 作品所屬單位 | 淡江大學資訊工程學系 |
| 出版者 | IEEE Systems, Man, and Cybernetics Society |
| 會議名稱 | |
| 會議地點 | Okayama, Japan |
| 摘要 | Background modeling is usually the first step in vision-based surveillance systems. Subsequent foreground segmentation can then be performed by comparing the variations between the current image and the reference background of the monitored scene. Various approaches have been proposed to deal with this issue. They differ in the type of background models used. However, these approaches emphasize only what the distribution of the background looks like, not what the real actions of the background are taken place during some period of time. In this paper, we propose a real-time background model that can automatically self-adjust to the scene changes. The experimental results show that the proposed background model has better performance over others in terms of noise suppression and the preservation of foreground details. In addition, our model can also operate correctly at night. Furthermore, it can effectively resist shaking of cameras and objects. |
| 關鍵字 | |
| 語言 | en |
| 收錄於 | |
| 會議性質 | 國際 |
| 校內研討會地點 | |
| 研討會時間 | 20090326~20090329 |
| 通訊作者 | |
| 國別 | JPN |
| 公開徵稿 | |
| 出版型式 | 紙本 電子版 |
| 出處 | Proceedings of the 2009 IEEE International Conference on Networking, Sensing and Control, pp.404-409 |
| 相關連結 |
機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/73244 ) |