Journal of Korea Multimedia Society (한국멀티미디어학회논문지)

Korea Multimedia Society (한국멀티미디어학회)
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Human Action Recognition Based on An Improved Combined Feature Representation

  • Zhang, Ning (Dept. of Information Communication Engineering, Tongmyong University) ;
  • Lee, Eung-Joo (Dept. of Information Communication Engineering, Tongmyong University)
  • Received : 2018.10.08
  • Accepted : 2018.11.01
  • Published : 2018.12.31
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Abstract

The extraction and recognition of human motion characteristics need to combine biometrics to determine and judge human behavior in the movement and distinguish individual identities. The so-called biometric technology, the specific operation is the use of the body's inherent biological characteristics of individual identity authentication, the most noteworthy feature is the invariance and uniqueness. In the past, the behavior recognition technology based on the single characteristic was too restrictive, in this paper, we proposed a mixed feature which combined global silhouette feature and local optical flow feature, and this combined representation was used for human action recognition. And we will use the KTH database to train and test the recognition system. Experiments have been very desirable results.

Keywords

MTMDCW_2018_v21n12_1473_f0001.png 이미지

Fig. 1. Background subtraction method.

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Fig. 2. Contour vector results.

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Fig. 3. Light flow diagram.

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Fig. 4. Optical flow feature extraction.

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Fig. 5. KTH database six action diagram.

Table 1. Select the recognition rate corresponding to the different characteristics

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Table 2. The different features combine the corresponding recognition rates

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  1. Human Motion Recognition Based on Spatio-temporal Convolutional Neural Network vol.23, pp.8, 2018, https://doi.org/10.9717/kmms.2020.23.8.977