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Mean-Shift Blob Clustering and Tracking for Traffic Monitoring System
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  • Mean-Shift Blob Clustering and Tracking for Traffic Monitoring System
  • Mean-Shift Blob Clustering and Tracking for Traffic Monitoring System
저자명
Choi. Jae-Young,Yang. Young-Kyu
간행물명
大韓遠隔探査學會誌
권/호정보
2008년|24권 3호|pp.235-243 (9 pages)
발행정보
대한원격탐사학회
파일정보
정기간행물|ENG|
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기타
이 논문은 한국과학기술정보연구원과 논문 연계를 통해 무료로 제공되는 원문입니다.
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기타언어초록

Object tracking is a common vision task to detect and trace objects between consecutive frames. It is also important for a variety of applications such as surveillance, video based traffic monitoring system, and so on. An efficient moving vehicle clustering and tracking algorithm suitable for traffic monitoring system is proposed in this paper. First, automatic background extraction method is used to get a reliable background as a reference. The moving blob(object) is then separated from the background by mean shift method. Second, the scale invariant feature based method extracts the salient features from the clustered foreground blob. It is robust to change the illumination, scale, and affine shape. The simulation results on various road situations demonstrate good performance achieved by proposed method.