Recent advances and trends in visual tracking: A review

Authors:
Hanxuan Yang;Ling Shao;Feng Zheng;Liang Wang;Zhan Song
Affiliations:
Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, China and Department of Electronic Engineering, South China Agricultural University, China;Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, China and Department of Electronic and Electrical Engineering, The University of Sheffield, UK;Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, China;National Lab of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, China;Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, China and The Chinese University of Hong Kong, Hong Kong, China
Venue:
Neurocomputing
Year:
2011

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Abstract

The goal of this paper is to review the state-of-the-art progress on visual tracking methods, classify them into different categories, as well as identify future trends. Visual tracking is a fundamental task in many computer vision applications and has been well studied in the last decades. Although numerous approaches have been proposed, robust visual tracking remains a huge challenge. Difficulties in visual tracking can arise due to abrupt object motion, appearance pattern change, non-rigid object structures, occlusion and camera motion. In this paper, we first analyze the state-of-the-art feature descriptors which are used to represent the appearance of tracked objects. Then, we categorize the tracking progresses into three groups, provide detailed descriptions of representative methods in each group, and examine their positive and negative aspects. At last, we outline the future trends for visual tracking research.