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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Jing-Ming Guo Chih-Sheng Hsu |
| Copyright Year | 2010 |
| Description | Author affiliation: Department of Electrical Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan (Jing-Ming Guo; Chih-Sheng Hsu) |
| Abstract | This study presents a new hierarchical scheme with coarse level and fine level for foreground detection using codebook model. The code book is mainly used to compress information to achieve high efficient processing speed. In the coarse level, six intensity values are employed to represent a block. The algorithm extends the concept of the Block Truncation Coding (BTC), and thus it can further improve processing efficiency. In detail, the coarse level is divided into two stages: Level one can increase processing speed and reduce noises without increasing False Positive (FP) rate; level two can increase detected precision of level one. Fine level can further enhance precision in coarse level. Moreover, this study also presents a new color model which can classify an input pixel as shadow, highlight, background, or foreground with the match function. This model can also cooperate with the Mixture of Gaussian (MOG) to remove shadow and thus enhances MOG's performance. As documented in the experimental results, the proposed algorithm can provide superior performance to that of the former Codebook (CB) approach. |
| Starting Page | 3441 |
| Ending Page | 3444 |
| File Size | 325876 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781424479924 |
| ISSN | 15224880 |
| e-ISBN | 9781424479948 |
| e-ISBN | 9781424479931 |
| DOI | 10.1109/ICIP.2010.5653862 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2010-09-26 |
| Publisher Place | Hong Kong |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Pixel Color Adaptation model Support vector machine classification Image color analysis Training Classification algorithms visual surveillance Background subtraction foreground detection shadow detection |
| Content Type | Text |
| Resource Type | Article |
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