Long-Term Tracking Based on Spatio-Temporal Context

doi:10.1007/s12204-017-1863-z

上海交通大学学报（英文版） ›› 2017, Vol. 22 ›› Issue (4): 504-512.doi: 10.1007/s12204-017-1863-z

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Long-Term Tracking Based on Spatio-Temporal Context

LU Jiahui (陆佳辉), CHEN Yimin* (陈一民), ZOU Yibo (邹一波), ZOU Guozhi (邹国志)

(School of Computer Engineering and Science, Shanghai University, Shanghai 200444, China)

出版日期:2017-08-03 发布日期:2017-08-03
通讯作者: CHEN Yimin (陈一民) E-mail:ymchen@mail.shu.edu.cn

Long-Term Tracking Based on Spatio-Temporal Context

LU Jiahui (陆佳辉), CHEN Yimin* (陈一民), ZOU Yibo (邹一波), ZOU Guozhi (邹国志)

(School of Computer Engineering and Science, Shanghai University, Shanghai 200444, China)

Online:2017-08-03 Published:2017-08-03
Contact: CHEN Yimin (陈一民) E-mail:ymchen@mail.shu.edu.cn

摘要/Abstract

摘要： Abstract: Aiming at the problem that the fast tracking algorithm using spatio-temporal context (STC) will inevitably lead to drift and even lose the target in long-term tracking, a new algorithm based on spatio-temporal context that integrates long-term tracking with detecting is proposed in this paper. We track the target by the fast tracking algorithm, and the cascaded search strategy is introduced to the detecting part to relocate the target if the fast tracking fails. To a large extent, the proposed algorithm effectively improves the accuracy and stability of long-term tracking. Extensive experimental results on benchmark datasets show that the proposed algorithm can accurately track and relocate the target though the target is partially or completely occluded or reappears after being out of the scene.

关键词: object tracking, spatio-temporal context (STC), object detection, cascaded search

Abstract: Abstract: Aiming at the problem that the fast tracking algorithm using spatio-temporal context (STC) will inevitably lead to drift and even lose the target in long-term tracking, a new algorithm based on spatio-temporal context that integrates long-term tracking with detecting is proposed in this paper. We track the target by the fast tracking algorithm, and the cascaded search strategy is introduced to the detecting part to relocate the target if the fast tracking fails. To a large extent, the proposed algorithm effectively improves the accuracy and stability of long-term tracking. Extensive experimental results on benchmark datasets show that the proposed algorithm can accurately track and relocate the target though the target is partially or completely occluded or reappears after being out of the scene.

Key words: object tracking, spatio-temporal context (STC), object detection, cascaded search

中图分类号:

TP 391

LU Jiahui (陆佳辉), CHEN Yimin* (陈一民), ZOU Yibo (邹一波), ZOU Guozhi (邹国志). Long-Term Tracking Based on Spatio-Temporal Context[J]. 上海交通大学学报（英文版）, 2017, 22(4): 504-512.

LU Jiahui (陆佳辉), CHEN Yimin* (陈一民), ZOU Yibo (邹一波), ZOU Guozhi (邹国志). Long-Term Tracking Based on Spatio-Temporal Context[J]. Journal of shanghai Jiaotong University (Science), 2017, 22(4): 504-512.

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Long-Term Tracking Based on Spatio-Temporal Context

Long-Term Tracking Based on Spatio-Temporal Context

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