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Furthermore, the boundary effects of correlation filters are suppressed by investigating background information so that the accuracy of the proposed tracker can be boosted. Experiments\u2019 empirical evaluations of 61 challenging benchmark sequences demonstrate that the overall tracking performance of the proposed tracker is very successfully improved. Moreover, our method obtains the top rank in performance by outperforming 17 state-of-the-art trackers on OTB2013.<\/jats:p>","DOI":"10.1142\/s0219691319500127","type":"journal-article","created":{"date-parts":[[2018,12,17]],"date-time":"2018-12-17T09:16:17Z","timestamp":1545038177000},"page":"1950012","source":"Crossref","is-referenced-by-count":0,"title":["Collaborative correlation filters for real-time tracking with spatial constraint"],"prefix":"10.1142","volume":"17","author":[{"given":"Lifang","family":"Zhou","sequence":"first","affiliation":[{"name":"College of Software Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, P. R. China"},{"name":"Hubei Key Laboratory of Intelligent Vision Based, Monitoring for Hydroelectric Engineering, Three Gorges University, Yichang 443002, P. R. China"},{"name":"College of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065, P. R. 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