전기학회논문지 (The Transactions of The Korean Institute of Electrical Engineers)

  • 제65권10호
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  • Pages.1731-1737
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  • 2016
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  • 1975-8359(pISSN)
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  • 2287-4364(eISSN)
대한전기학회 (The Korean Institute of Electrical Engineers)
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시공간 템플릿과 컨볼루션 신경망을 사용한 깊이 영상 기반의 사람 행동 인식

Depth Image-Based Human Action Recognition Using Convolution Neural Network and Spatio-Temporal Templates

  • Eum, Hyukmin (Dept. of Electrical and Electronic Engineering, Yonsei University) ;
  • Yoon, Changyong (Dept. of Electrical Engineering, Suwon Science College)
  • 투고 : 2016.06.10
  • 심사 : 2016.09.01
  • 발행 : 2016.10.01
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초록

In this paper, a method is proposed to recognize human actions as nonverbal expression; the proposed method is composed of two steps which are action representation and action recognition. First, MHI(Motion History Image) is used in the action representation step. This method includes segmentation based on depth information and generates spatio-temporal templates to describe actions. Second, CNN(Convolution Neural Network) which includes feature extraction and classification is employed in the action recognition step. It extracts convolution feature vectors and then uses a classifier to recognize actions. The recognition performance of the proposed method is demonstrated by comparing other action recognition methods in experimental results.

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참고문헌

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