Adaptive Slice Representation for Human Action Classification
Shan, Yanhu; Zhang, Zhang; Yang, Peipei; Huang, Kaiqi; Kaiqi Huang
2015-10-01
发表期刊IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY
卷号25期号:10页码:1624-1636
文章类型Article
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.
关键词Action Recognition Adaptive Slice Mel Frequency Cepstrum Coefficient (Mfcc) Minimum Average Entropy (Minae)
WOS标题词Science & Technology ; Technology
DOI10.1109/TCSVT.2014.2376136
关键词[WOS]ACTION RECOGNITION ; BEHAVIOR ANALYSIS ; MOTION ; DESCRIPTORS ; TRACKING ; DENSE
收录类别SCI
语种英语
WOS研究方向Engineering
WOS类目Engineering, Electrical & Electronic
WOS记录号WOS:000362358300006
引用统计
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/10037
专题模式识别国家重点实验室_模式分析与学习
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.
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