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基于深度信息的特征学习与动作识别方法.
- Source :
-
Application Research of Computers / Jisuanji Yingyong Yanjiu . Nov2021, Vol. 38 Issue 11, p3446-3450. 5p. - Publication Year :
- 2021
-
Abstract
- In order to recognize complex interactive actions, this paper proposed a feature learning method based on depth information, and used a two-layer classification strategy to solve similar action recognition problems. The method analyzed the depth image action sequence from the frequency domain, extracted the frequency domain features, used VAE for spatial feature compression representation, established HMM to simulate time series changes and performed the first layer action recognition. In order to solve the problem of similar actions, this paper introduced three-dimensional joint point features for the second layer action recognition. Experimental results show that these two types of features can effectively represent the meaning of gestures on the SBU-Kinect action data set, the strategy is simple and effective and can get high recognition accuracy. [ABSTRACT FROM AUTHOR]
- Subjects :
- *TIME series analysis
*PROBLEM solving
*MARKOV processes
*GESTURE
Subjects
Details
- Language :
- Chinese
- ISSN :
- 10013695
- Volume :
- 38
- Issue :
- 11
- Database :
- Academic Search Index
- Journal :
- Application Research of Computers / Jisuanji Yingyong Yanjiu
- Publication Type :
- Academic Journal
- Accession number :
- 155349332
- Full Text :
- https://doi.org/10.19734/j.issn.1001-3695.2021.01.0067