Multi-target tracking based on on-line boosting is a significant technique in computer vision. However, it is very difficult to select the optimal classifier in on-line learning process since tracking often relies on an assumption that the appearance model of target is fixed. This would directly lead to a decline in the performance of on-line boosting. In this paper, we presents a novel on-line multi-target tracking framework based on Weighted Incremental Histogram Model (called WIHM), which can be applied in some static or dynamic scenarios. First, we propose a novel method—WIHM, which is employed to obtain the optimal size of a tracked object. Second, a new update scheme is used to reach local optimum tracking appearance model with high possibility and accuracy. Third, based on the above works, a multi-target tracking framework is proposed to track multi-targets simultaneously. With the appearance model of targets changed continually, our represented approach can track these targets more powerful, especially in dealing with camera motions. Experimental results show the effectiveness and robustness of our method.
보안공학연구지원센터(IJSIP) [Science & Engineering Research Support Center, Republic of Korea(IJSIP)]
설립연도
2006
분야
공학>컴퓨터학
소개
1. 보안공학에 대한 각종 조사 및 연구
2. 보안공학에 대한 응용기술 연구 및 발표
3. 보안공학에 관한 각종 학술 발표회 및 전시회 개최
4. 보안공학 기술의 상호 협조 및 정보교환
5. 보안공학에 관한 표준화 사업 및 규격의 제정
6. 보안공학에 관한 산학연 협동의 증진
7. 국제적 학술 교류 및 기술 협력
8. 보안공학에 관한 논문지 발간
9. 기타 본 회 목적 달성에 필요한 사업
간행물
간행물명
International Journal of Signal Processing, Image Processing and Pattern Recognition
간기
격월간
pISSN
2005-4254
수록기간
2008~2016
십진분류
KDC 505DDC 605
이 권호 내 다른 논문 / International Journal of Signal Processing, Image Processing and Pattern Recognition Vol.7 No.1