A Basic Study on the Instance Segmentation with Surveillance Cameras at Construction Sties using Deep Learning based Computer Vision

건설 현장 CCTV 영상에서 딥러닝을 이용한 사물 인식 기초 연구

  • 강경수 (삼육대학교 건설기술및관리연구소) ;
  • 조영운 (삼육대학교 건설기술및관리연구소) ;
  • 류한국 (삼육대학교 건축학과)
  • Published : 2020.11.12

Abstract

The construction industry has the highest occupational fatality and injury rates related to accidents of any industry. Accordingly, safety managers closely monitor to prevent accidents in real-time by installing surveillance cameras at construction sites. However, due to human cognitive ability limitations, it is impossible to monitor many videos simultaneously, and the fatigue of the person monitoring surveillance cameras is also very high. Thus, to help safety managers monitor work and reduce the occupational accident rate, a study on object recognition in construction sites was conducted through surveillance cameras. In this study, we applied to the instance segmentation to identify the classification and location of objects and extract the size and shape of objects in construction sites. This research considers ways in which deep learning-based computer vision technology can be applied to safety management on a construction site.

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Acknowledgement

본 논문은 2020년 정부(과학기술정보통신부)의 재원으로 한국연구재단의 지원을 받아 수행된 연구임을 밝히며 이에 감사를 드립니다. (No. 2020R1A2B5B01001609)