Journal of Digital Contents Society (디지털콘텐츠학회 논문지)

Digital Contents Society (한국디지털콘텐츠학회)
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Relation Tracking of Occluded objects using a Perspective Depth

투시적 깊이를 활용한 중첩된 객체의 관계추적

  • Received : 2015.12.10
  • Accepted : 2015.12.29
  • Published : 2015.12.31
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Abstract

Networked multiple CCTV systems are required to effectively trace down long-term abnormal behaviors, such as stalking. However, the occluding event, which often takes place during tracking, may result in critical errors of cessation of tracing, or tracking wrong objects. Thus, utilizing installed regular CCTVs, this study aims to trace the relation tracking in a continuous manner by recognizing distinctive features of each object and its perspective projection depth to address the problem with occluded objects. In addition, this study covers occlusion event between the stationary background objects, such as street lights, or walls, and the targeted object.

스토킹과 같은 장시간 동안의 이상행위를 추적하기 위해선 네트워크로 연결된 다중 CCTV환경하에서 객체간의 관계를 지속적으로 추적하는 시스템이 매우 필요하다. 그러나 추적과정에서 자주 발생하는 객체의 겹침문제가 해결되지 않는다면 객체 추적이 중단되거나 다른 객체로 대체되는 등의 치명적인 오류가 발생할 가능성이 농후하다. 본 연구는 기 설치된 CCTV를 최대한 활용하기 위해 투시적 투영깊이 및 객체특성을 활용하여 겹침문제를 해결함으로써 중첩된 객체 관계를 지속적으로 추적가능하게 한다. 객체간 겹침문제 뿐만 아니라 배경에 포함된 객체 즉 벽이나 기둥 등의 객체와의 겹침문제도 함께 다룬다.

Keywords

References

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