Object Tracking: A Survey

Object Tracking: A Survey (2006)

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by Alper Yilmaz , Omar Javed , Mubarak Shah

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Datum	Value	Source
TITLE	Object Tracking: A Survey	user correction
AUTHOR NAME	Alper Yilmaz	user correction
AUTHOR AFFIL	Ohio State University	user correction
AUTHOR NAME	Omar Javed	user correction
AUTHOR AFFIL	ObjectVideo, Inc.	user correction
AUTHOR ADDR	Reston, VA 20191	user correction
AUTHOR NAME	Mubarak Shah	user correction
AUTHOR AFFIL	School of EECS, University of Central Florida	user correction
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.	SVM HeaderParse 0.2
YEAR	2006	user correction
CITATIONS	159 found	ParsCit 1.0