An HMM-based segmentation method for traffic monitoring movies

被引：61

作者：

Kato, J ^{[1
]}

Watanabe, T

Joga, S

Rittscher, J

Blake, A

机构：

[1] Nagoya Univ, Dept Informat Engn, Chikusa Ku, Nagoya, Aichi 4648603, Japan

[2] France Telecome R&D, DMR RMO, F-92794 Issy Les Moulineaux 9, France

[3] GE Corp Res & Dev, Visualizat & Comp Vis Lab, Schenectady, NY 12301 USA

[4] Microsoft Res, Cambridge CB2 0FB, England

来源：

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE | 2002年 / 24卷 / 09期

关键词：

car tracking; hidden Markov model; image classification; image segmentation; wavelet coefficients;

D O I：

10.1109/TPAMI.2002.1033221

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Shadows of moving objects often obstruct robust visual tracking. We propose an HMM-based segmentation method which classifies in real time each pixel or region into three categories: shadows, foreground, and background objects. In the case of traffic monitoring movies, the effectiveness of the proposed method has been proven through experimental results.

引用

页码：1291 / 1296

页数：6

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