DOI QR코드

DOI QR Code

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)
  • 투고 : 2018.10.08
  • 심사 : 2018.11.01
  • 발행 : 2018.12.31

초록

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.

키워드

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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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참고문헌

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피인용 문헌

  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