Path detection in video surveillance

被引：109

作者：

Makris, D ^{[1
]}

Ellis, T ^{[1
]}

机构：

[1] City Univ London, Informat Engn Ctr, London EC1V 0HB, England

来源：

IMAGE AND VISION COMPUTING | 2002年 / 20卷 / 12期

基金：

英国工程与自然科学研究理事会;

关键词：

people tracking; learning paths; scene labelling; route detection; track prediction; video annotation;

D O I：

10.1016/S0262-8856(02)00098-7

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 addresses the problem of automatically extracting frequently used pedestrian pathways from video sequences of natural outdoor scenes. Path models are learnt from the accumulation of trajectory data over long time periods, and can be used to augment the classification of subsequent track data. In particular, labelled paths provide an efficient means for compressing the trajectory data for logging purposes. In addition, the model can be used to compute a probabilistic prediction of the pedestrian's location many time steps ahead, and to aid the recognition of unusual behaviour identified as atypical object motion. (C)2002 Elsevier Science B.V. All rights reserved.

引用

页码：895 / 903

页数：9