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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Yuanyuan Zhang Xiaojuan Wu Tingting Guo Xiuyuan Li Qiuqi Ruan |
| Copyright Year | 2009 |
| Description | Author affiliation: School of Information Science & Engineering, Shandong University, Jinan, China (Yuanyuan Zhang; Xiaojuan Wu; Tingting Guo; Xiuyuan Li) || Institute of Information Science, Beijing Jiaotong University, China (Qiuqi Ruan) |
| Abstract | An integrated silhouette with perfect appearance is helpful for gait recognition. However, the silhouettes often have holes or missing parts, because the commonly used motion detection and extraction methods are not always suitable for every case. A robust post-processing strategy is proposed here to refine the raw silhouettes. First, an individual silhouette model which represents the mutual characteristic of a certain sequence is trained to update the current sequence. Then a population silhouette model which represents the mutual characteristic of all sequences in the dataset is trained to update the sequences that need further refinement. The experiments on NLPR database show that the proposed algorithm is quite effective and helps the existing recognition method to achieve higher classification performance. |
| Starting Page | 476 |
| Ending Page | 479 |
| File Size | 152045 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781424445196 |
| DOI | 10.1109/ICCSIT.2009.5234506 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2009-08-08 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Biometrics Computer vision gait recognition Humans individual model Fingerprint recognition silhouette refinement Data mining Information science Layout population model Robustness Motion detection Pixel |
| Content Type | Text |
| Resource Type | Article |
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