제어로봇시스템학회논문지 (Journal of Institute of Control, Robotics and Systems)

  • 제15권5호
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  • Pages.505-510
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  • 2009
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  • 1976-5622(pISSN)
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  • 2233-4335(eISSN)
제어로봇시스템학회 (Institute of Control, Robotics and Systems)
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감시용 로봇의 시각을 위한 인공 신경망 기반 겹친 사람의 구분

Dividing Occluded Humans Based on an Artificial Neural Network for the Vision of a Surveillance Robot

  • 도용태 (대구대학교 전자공학부)
  • 발행 : 2009.05.01
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초록

In recent years the space where a robot works has been expanding to the human space unlike traditional industrial robots that work only at fixed positions apart from humans. A human in the recent situation may be the owner of a robot or the target in a robotic application. This paper deals with the latter case; when a robot vision system is employed to monitor humans for a surveillance application, each person in a scene needs to be identified. Humans, however, often move together, and occlusions between them occur frequently. Although this problem has not been seriously tackled in relevant literature, it brings difficulty into later image analysis steps such as tracking and scene understanding. In this paper, a probabilistic neural network is employed to learn the patterns of the best dividing position along the top pixels of an image region of partly occlude people. As this method uses only shape information from an image, it is simple and can be implemented in real time.

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참고문헌

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피인용 문헌

  1. A Taxonomy of Vision Systems for Ground Mobile Robots vol.11, pp.7, 2014, https://doi.org/10.5772/58900