caa a22 4500 605540616 CHVBK 20210128100912.0 cr unu---uuuuu 210128e20151001xx s 000 0 eng 10.1007/s00371-014-1012-8 doi (NATIONALLICENCE)springer-10.1007/s00371-014-1012-8 Robust object tracking with active context learning [Elektronische Daten] [Wei Quan, Yongquan Jiang, Jianjun Zhang, Jim Chen] This paper proposes a method to deal with long-term robust object tracking in unconstrained environment. The approach exploits both target and background information on the fly automatically. It builds the structural constraint using active context learning to enhance the adaptability for variation of the target and stability of tracking. An optical-flow-based motion region extraction method is integrated into the context learning framework to address the problem of fast target motion or abrupt camera motion. Experimental results on challenging real-world video sequences demonstrate the effectiveness and robustness of our approach. Comparisons with several state-of-the-art methods are provided. Springer-Verlag Berlin Heidelberg, 2014 Object tracking nationallicence Active context learning nationallicence Online model nationallicence Quan Wei School of Electrical Engineering, Southwest Jiaotong University, 610031, Chengdu, Sichuan, People's Republic of China aut Jiang Yongquan State Key Laboratory of Traction Power, Southwest Jiaotong University, 610031, Chengdu, Sichuan, People's Republic of China aut Zhang Jianjun State Key Laboratory of Traction Power, Southwest Jiaotong University, 610031, Chengdu, Sichuan, People's Republic of China aut Chen Jim State Key Laboratory of Traction Power, Southwest Jiaotong University, 610031, Chengdu, Sichuan, People's Republic of China aut The Visual Computer Springer Berlin Heidelberg 31/10(2015-10-01), 1307-1318 0178-2789 31:10<1307 2015 31 371 https://doi.org/10.1007/s00371-014-1012-8 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00371-014-1012-8 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Quan Wei School of Electrical Engineering, Southwest Jiaotong University, 610031, Chengdu, Sichuan, People's Republic of China aut NATIONALLICENCE 700 1- Jiang Yongquan State Key Laboratory of Traction Power, Southwest Jiaotong University, 610031, Chengdu, Sichuan, People's Republic of China aut NATIONALLICENCE 700 1- Zhang Jianjun State Key Laboratory of Traction Power, Southwest Jiaotong University, 610031, Chengdu, Sichuan, People's Republic of China aut NATIONALLICENCE 700 1- Chen Jim State Key Laboratory of Traction Power, Southwest Jiaotong University, 610031, Chengdu, Sichuan, People's Republic of China aut NATIONALLICENCE 773 0- The Visual Computer Springer Berlin Heidelberg 31/10(2015-10-01), 1307-1318 0178-2789 31:10<1307 2015 31 371