Details of Research Outputs

TitleVisual tracking by using kalman gradient vector flow (kgvf) snakes
Creator
Date Issued2004
Conference Name8th International Conference on Knowledge-Based Intelligent Information and Engineering Systems
Source PublicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISBN3540232060
ISSN0302-9743
Volume3214
Pages557-563
Conference DateSEP, 2004
Conference PlaceWellington Inst Technol, Wellington, NEW ZEALAND
Abstract

In this paper, we propose a new tracking model called Kalman Gradient Vector Flow (KGVF) snakes. KGVF snakes employ the Gradient Vector Flow (GVF) model [9] with the Kalman Filter [4] for object tracking. GVF model is an active contour model that used gradient vector flow field as the external force. This force ensures a larger capture range in the model and stronger ability to contract to the object boundary. Kaiman Filter is an estimation algorithm that can be used in stochastic environment. In this paper, we explain how KGVF snakes works and also we have done some experiments to show how KGVF snakes have a strong tracking ability in clutter scenes. © Springer-Verlag 2004.

DOI10.1007/978-3-540-30133-2_73
URLView source
Indexed BySCIE ; CPCI-S
Language英语English
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence ; Computer Science, Information Systems
WOS IDWOS:000224585400073
Scopus ID2-s2.0-35048877211
Citation statistics
Cited Times [WOS]:0   [WOS Record]     [Related Records in WOS]
Document TypeConference paper
Identifierhttp://repository.uic.edu.cn/handle/39GCC9TT/7917
CollectionResearch outside affiliated institution
Corresponding AuthorLam, Toby H.W.
Affiliation
Department of Computing,Hong Kong Polytechnic University Hung Hum,Kowloon,Hong Kong
Recommended Citation
GB/T 7714
Lam, Toby H.W.,Lee, Raymond S.T. Visual tracking by using kalman gradient vector flow (kgvf) snakes[C], 2004: 557-563.
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