Active contours for tracking distributions

被引：137

作者：

Freedman, D ^{[1
]}

Zhang, T ^{[1
]}

机构：

[1] Rensselaer Polytech Inst, Dept Comp Sci, Troy, NY 12180 USA

来源：

IEEE TRANSACTIONS ON IMAGE PROCESSING | 2004年 / 13卷 / 04期

基金：

美国国家科学基金会;

关键词：

active contours; Bhattacharyya measure; Kullback-Leibler distance; level set method; partial differential equations; visual tracking;

D O I：

10.1109/TIP.2003.821445

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

A new approach to tracking using active contours is presented. The class of objects to be tracked is assumed to be characterized by a probability distribution over some variable, such as intensity, color, or texture. The goal of the algorithm is to find the region within the current image, such that the sample distribution of the interior of the region most closely matches the model distribution. Two separate criteria for matching distributions are examined, and the curve evolution equations are derived in each case. The flows are shown to perform well in experiments.

引用

页码：518 / 526

页数：9

共 29 条

[1] AMINI AA, 1988, P 2 INT C COMP VIS, P95
[2] [Anonymous], P IEEE INT C COMP VI
[3] [Anonymous], P 3 IEEE WORKSH WAC
[4] Real time face and object tracking as a component of a perceptual user interface
Bradski, GR
[J]. FOURTH IEEE WORKSHOP ON APPLICATIONS OF COMPUTER VISION - WACV'98, PROCEEDINGS, 1998, : 214 - 219
[5] Geodesic active contours
Caselles, V
Kimmel, R
Sapiro, G
[J]. INTERNATIONAL JOURNAL OF COMPUTER VISION, 1997, 22 (01) : 61 - 79
[6] A GEOMETRIC MODEL FOR ACTIVE CONTOURS IN IMAGE-PROCESSING
CASELLES, V
CATTE, F
COLL, T
DIBOS, F
[J]. NUMERISCHE MATHEMATIK, 1993, 66 (01) : 1 - 31
[7] Deformable boundary finding in medical images by integrating gradient and region information
Chakraborty, A
Staib, LH
Duncan, JS
[J]. IEEE TRANSACTIONS ON MEDICAL IMAGING, 1996, 15 (06) : 859 - 870
[8] Active contours without edges
Chan, TF
Vese, LA
[J]. IEEE TRANSACTIONS ON IMAGE PROCESSING, 2001, 10 (02) : 266 - 277
[9] A level set algorithm for minimizing the Mumford-Shah functional in image processing
Chan, TF
Vese, LA
[J]. IEEE WORKSHOP ON VARIATIONAL AND LEVEL SET METHODS IN COMPUTER VISION, PROCEEDINGS, 2001, : 161 - 168
[10] Kernel-based object tracking
Comaniciu, D
Ramesh, V
Meer, P
[J]. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2003, 25 (05) : 564 - 577

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