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Fast Motion Detection Based on Accumulative Optical Flow and Double Background Model.

Authors :
Yue Hao
Jiming Liu
Yu-Ping Wang
Yiu-ming Cheung
Hujun Yin
Licheng Jiao
Jianfeng Ma
Yong-Chang Jiao
Jin Zheng
Bo Li
Bing Zhou
Wei Li
Source :
Computational Intelligence & Security (9783540308195); 2005, p291-296, 6p
Publication Year :
2005

Abstract

Optical flow and background subtraction are important methods for detecting motion in video sequences. This paper integrates the advantages of these two methods. Firstly, proposes a high precise algorithm for optical flow computation with analytic wavelet and M-estimator to solve the optical flow restricted equations. Secondly, introduces the extended accumulative optical flow and also provides its computational strategies, then obtains a robust motion detection algorithm. Furthermore, combines a background subtraction algorithm based on the double background model with the extended accumulative optical flow to give an abnormity alarm in time. All obvious proofs of experiments show that, our algorithm can precisely detect moving objects, no matter slow or little, preferably solve the occlusions as well as give an alarm fast. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISBNs :
9783540308195
Database :
Supplemental Index
Journal :
Computational Intelligence & Security (9783540308195)
Publication Type :
Book
Accession number :
32885739
Full Text :
https://doi.org/10.1007/11596981_43