Structure Sparsity for Multi-camera Gait Recognition | |
Qiyue Yin1![]() ![]() ![]() | |
2012 | |
会议名称 | Chinese Conference on Pattern Recognition |
页码 | 259-267 |
会议日期 | 2012-9-24 |
会议地点 | 中国北京 |
摘要 |
With the rapid development of surveillance technology, there are often several cameras in one scenario. The multi-camera usage to perform gait recognition becomes a challenge problem. This paper studies multi-camera gait recognition via structure sparsity. For the multicamera structure in the training set, we propose a structure sparsity algorithm to learn informative and discriminative sparse representations; and for the structure in the testing set, we develop a new classification criteria based on the reconstruction error of learned sparse representations. In addition, we learn a dictionary from the original gait data to further improve recognition accuracy meanwhile reduce computational cost. Experimental results show that the proposed method can efficiently deal with the multi-camera gait recognition problem and outperforms the state-of-the-art sparse representation methods. |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/14074 |
专题 | 模式识别实验室 |
作者单位 | 1.哈尔滨工程大学 2.中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Qiyue Yin,Rong Sun,Liang Wang,et al. Structure Sparsity for Multi-camera Gait Recognition[C],2012:259-267. |
条目包含的文件 | 下载所有文件 | |||||
文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
Structured sparsity (256KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。
修改评论