로봇학회논문지 (The Journal of Korea Robotics Society)

  • 제15권4호
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  • Pages.385-391
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  • 2020
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  • 1975-6291(pISSN)
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  • 2287-3961(eISSN)
한국로봇학회 (Korea Robotics Society)
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행동 인식을 위한 시공간 앙상블 기법

Spatial-temporal Ensemble Method for Action Recognition

  • 투고 : 2020.07.08
  • 심사 : 2020.08.13
  • 발행 : 2020.11.30
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초록

As deep learning technology has been developed and applied to various fields, it is gradually changing from an existing single image based application to a video based application having a time base in order to recognize human behavior. However, unlike 2D CNN in a single image, 3D CNN in a video has a very high amount of computation and parameter increase due to the addition of a time axis, so improving accuracy in action recognition technology is more difficult than in a single image. To solve this problem, we investigate and analyze various techniques to improve performance in 3D CNN-based image recognition without additional training time and parameter increase. We propose a time base ensemble using the time axis that exists only in the videos and an ensemble in the input frame. We have achieved an accuracy improvement of up to 7.1% compared to the existing performance with a combination of techniques. It also revealed the trade-off relationship between computational and accuracy.

키워드

참고문헌

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피인용 문헌

  1. 밝기 변화에 강인한 적대적 음영 생성 및 훈련 글자 인식 알고리즘 vol.16, pp.3, 2020, https://doi.org/10.7746/jkros.2021.16.3.276