Title

Object Tracking: A Survey

Keywords

Appearance models; Contour evolution; Feature selection; Object detection; Object representation; Point tracking; Shape tracking

Abstract

The goal of this article is to review the state-of-the-art tracking methods, classify them into different categories, and identify new trends. Object tracking, in general, is a challenging problem. Difficulties in tracking objects can arise due to abrupt object motion, changing appearance patterns of both the object and the scene, nonrigid object structures, object-to-object and object-to-scene occlusions, and camera motion. Tracking is usually performed in the context of higher-level applications that require the location and/or shape of the object in every frame. Typically, assumptions are made to constrain the tracking problem in the context of a particular application. In this survey, we categorize the tracking methods on the basis of the object and motion representations used, provide detailed descriptions of representative methods in each category, and examine their pros and cons. Moreover, we discuss the important issues related to tracking including the use of appropriate image features, selection of motion models, and detection of objects. © 2006 ACM.

Publication Date

12-25-2006

Publication Title

ACM Computing Surveys

Volume

38

Issue

4

Number of Pages

-

Document Type

Review

Personal Identifier

scopus

DOI Link

https://doi.org/10.1145/1177352.1177355

Socpus ID

33846013241 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/33846013241

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