Recent advances and trends in visual tracking: A review

Hanxuan Yang, Ling Shao, Feng Zheng, Liang Wang, Zhan Song

Research output: Contribution to journalArticlepeer-review

534 Citations (Scopus)

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.
Original languageEnglish
Pages (from-to)3823-3831
JournalNeurocomputing
Volume74
Issue number18
Early online date24 Aug 2011
DOIs
Publication statusPublished - Nov 2011

Fingerprint

Dive into the research topics of 'Recent advances and trends in visual tracking: A review'. Together they form a unique fingerprint.

Cite this