DocumentCode
2379381
Title
Gaussian mixture classification for moving object detection in video surveillance environment
Author
Carminati, Lionel ; Benois-Pineau, Jenny
Author_Institution
LaBRI CNRS UMR, France
Volume
3
fYear
2005
fDate
11-14 Sept. 2005
Abstract
The paper deals with detection of moving objects by modelling pixel grey level distribution along the time. The detection of moving objects is based on learning and update of background pixel distributions. The choice of appropriate mixture´s component for a given pixel is performed by likelihood maximization. An original Markov regularization is proposed to smooth detection. The method performs in real time on CIF resolution video and low cost commercial hardware.
Keywords
Gaussian processes; Markov processes; image classification; image resolution; object detection; video signal processing; Gaussian mixture classification; Markov regularization; background pixel distributions; grey level distribution; likelihood maximization; moving object detection; video surveillance environment; Cameras; Costs; Encoding; Hardware; Man machine systems; Object detection; Pixel; Real time systems; Stochastic processes; Video surveillance;
fLanguage
English
Publisher
ieee
Conference_Titel
Image Processing, 2005. ICIP 2005. IEEE International Conference on
Print_ISBN
0-7803-9134-9
Type
conf
DOI
10.1109/ICIP.2005.1530341
Filename
1530341
Link To Document