Video object motion segmentation for intelligent visual surveillance

被引：0

作者：

Jiang, M. ^{[1
]}

Crookes, D. ^{[1
]}

机构：

[1] Queens Univ Belfast, Sch Elect Engn Elect & Comp Sci, Inst Elect Commun & Informat Technol, Belfast BT3 9DT, Antrim, North Ireland

来源：

IMVIP 2007: INTERNATIONAL MACHINE VISION AND IMAGE PROCESSING CONFERENCE, PROCEEDINGS | 2007年

关键词：

D O I：

10.1109/IMVIP.2007.7

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper presents a video object motion segmentation method for object tracking in visual surveillance. In the first step, the frames are first decomposed into small facets (regions), using colour information. Then, based on the detected motion, the motion segmentation is performed at facet level. A Bayesian approach is applied in clustering facets into moving objects and tracking moving video objects. Experiments have verified that the proposed method can efficiently tackle the complexity of video motion tracking.

引用

页码：202 / 202

页数：1

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