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Alternative TitleHuman Action Recognition Based on Pose Spatio-Temporal Features
郑潇; 彭晓东; 王嘉璇
Source Publication计算机辅助设计与图形学学报
Keyword行为识别 姿态时空特征 Fisher向量 加权融合
Other AbstractIn order to extract human motion information efficiently and improve the accuracy of action recognition from videos, an approach for action recognition based on human pose spatio-temporal features is proposed. Firstly, with the joint positions of human body in each frame of the video acquired, we extracted pose information by handcrafted features. Specifically, the positions of joints and relatives in the spatial dimension, as well as the change of that in the temporal dimension were calculated. The two together constituted human pose spatiotemporal feature descriptors. Then the Fisher Vector model was utilized to compute fixed dimension Fisher vector for each descriptor separately. Lastly, features were weighted to fusion for classification. Experimental results show that the proposed algorithm can effectively improve action recognition performance.
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Cited Times:1[CSCD]   [CSCD Record]
Document Type期刊论文
Recommended Citation
GB/T 7714
郑潇,彭晓东,王嘉璇. 基于姿态时空特征的人体行为识别方法[J]. 计算机辅助设计与图形学学报,30(9):1615-1624.
APA 郑潇,彭晓东,&王嘉璇.
MLA 郑潇,et al."基于姿态时空特征的人体行为识别方法".计算机辅助设计与图形学学报 30.9
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