Adaptive Slice Representation for Human Action Classification
文献类型：期刊论文
| 作者 | Shan, Yanhu ; Zhang, Zhang; Yang, Peipei; Huang, Kaiqi; Kaiqi Huang
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| 刊名 | IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY
 |
| 出版日期 | 2015-10-01 |
| 卷号 | 25期号:10页码:1624-1636 |
| 关键词 | Action recognition adaptive slice mel frequency cepstrum coefficient (MFCC) minimum average entropy (MinAE) |
| 英文摘要 | Common action recognition methods describe an action sequence along with its time axis, i.e., first extracting features from the x y plane, and then modeling the dynamic changes along with the time axis. Other than the ordinary x y plane-based representation, other views, e.g., xt slice-based representation, may be more efficient to distinguish different actions. In this paper, we investigate different slicing views of the spatiotemporal volume to organize action sequences and propose an efficient slice representation for human action recognition. First, a minimum average entropy principle is proposed to select the optimal slicing angle for each action sequence adaptively. This allows the foreground pixels to be distributed in the fewest slices so as to reduce more uncertainty caused by the information dispersed in different slices. Then, the obtained slice sequence is transformed into a pair of 1-D signals to describe the distribution of foreground pixels along the time axis. Finally, the mel frequency cepstrum coefficient features are calculated to describe the spectrum characteristics of the 1-D signals over time. Thus, a 3-D spatiotemporal action volume is efficiently transformed into a low-dimensional spectrum features. Extensive experiments on the 2-D human action data sets (the UIUC and the WEIZ-MANN) as well as the Microsoft Research (MSR) Action3-D depth data set demonstrate the effectiveness of the slice-based representation, where the recognition performance can reach to the state-of-the-art level with high efficiency. |
| WOS标题词 | Science & Technology ; Technology |
| 类目[WOS] | Engineering, Electrical & Electronic |
| 研究领域[WOS] | Engineering |
| 关键词[WOS] | ACTION RECOGNITION ; BEHAVIOR ANALYSIS ; MOTION ; DESCRIPTORS ; TRACKING ; DENSE |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS记录号 | WOS:000362358300006 |
| 公开日期 | 2015-12-24 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/10037]  |
| 专题 | 自动化研究所_模式识别国家重点实验室_模式分析与学习团队 |
| 通讯作者 | Kaiqi Huang |
| 作者单位 | Chinese Acad Sci, Inst Automat, Ctr Res Intelligent Percept & Comp, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China |
| 推荐引用方式 GB/T 7714 | Shan, Yanhu,Zhang, Zhang,Yang, Peipei,et al. Adaptive Slice Representation for Human Action Classification[J]. IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY,2015,25(10):1624-1636. |
| APA | Shan, Yanhu,Zhang, Zhang,Yang, Peipei,Huang, Kaiqi,&Kaiqi Huang.(2015).Adaptive Slice Representation for Human Action Classification.IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY,25(10),1624-1636. |
| MLA | Shan, Yanhu,et al."Adaptive Slice Representation for Human Action Classification".IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 25.10(2015):1624-1636. |
入库方式： OAI收割
来源：自动化研究所
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