JOURNAL ARTICLE

Real Time Object Tracking Method using Multiple Cameras

In-Tae JangDong‐Woo KimYoungjun SongHyeok-Bong KwonJae-Hyeong Ahn

Year: 2012 Journal:   Journal of the Korea Industrial Information Systems Research Vol: 17 (4)Pages: 51-59

Abstract

최근 보안 감시 분야에서 영상처리를 이용한 객체 추적에 관한 연구가 활발히 이루어지고 있다. 기존 여러 대의 카메라를 이용한 보안 감시 시스템은 각각 독립적으로 운영되었다. 따라서 추적 객체가 다른 카메라의 감시영역으로 이동 시 계속해서 추적이 어려웠다. 이 문제를 해결하기 위해 본 논문은 다중 카메라에서 객체의 이동방향에 따라 자동으로 카메라의 제어권을 변경하는 방법을 제안한다. 제안방법은 객체를 검출하고 객체의 색상 정보와 방향 정보로 객체를 추적한다. 색상 정보는 hue를 이용하고 방향 정보는 광류를 이용하여 획득한다. 이때 광류는 전체 영상이 아닌 객체가 검출된 영역에만 적용하여 계산량을 줄여 실시간 추적이 가능하게 한다. 또한, 자동으로 객체를 추적함으로써 기존 카메라를 이용한 보안 감시 시스템의 불편함을 해결할 수 있다. Recently, the study about object tracking using image processing has been active in the field of security and surveillance. Existing security and surveillance systems using multiple cameras have been operating independently. Thus, the chase was difficult when the tracking object move to other monitored areas. In this paper, we propose the way to change the control of camera automatically following the moving direction of objects in multiple cameras. The proposed method detects the object and tracks the object using color information and direction information of object. The color information obtains using the hue and the direction information obtains using the optical flow. At this time, the optical flow is detected for the entire image area of an object that is not applied only to reduce the computational complexity makes it possible to track in real time. In addition, it can be solved to inconvenience of security surveillance system to use existing camera by tracking an object automatically.

Keywords:
Computer vision Artificial intelligence Computer science Object (grammar) Hue Tracking (education) Video tracking Optical flow Object detection Track (disk drive) Image (mathematics) Pattern recognition (psychology)

Metrics

3
Cited By
0.83
FWCI (Field Weighted Citation Impact)
4
Refs
0.76
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Video Surveillance and Tracking Methods
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Remote Sensing and Land Use
Physical Sciences →  Earth and Planetary Sciences →  Atmospheric Science
Internet of Things and Social Network Interactions
Physical Sciences →  Computer Science →  Computer Networks and Communications

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