DocumentCode :
3039070
Title :
Coarse-to-fine strategy for robust and efficient change detectors
Author :
Bevilacqua, A. ; Stefano, L. Di ; Lanza, A.
Author_Institution :
Dept. of Electron., Comput. Sci. & Syst., Bologna Univ., Italy
fYear :
2005
fDate :
15-16 Sept. 2005
Firstpage :
87
Lastpage :
92
Abstract :
We present a novel approach to change detection based on a coarse-to-fine strategy. An efficient coarse-level detection is proposed that filters out most of the possible false changes, thus attaining reliable and tight coarse-grain super-masks of the truly changed areas. The subsequent fine-level detection can thus "focus the attention" just on the "interesting" parts of the frame and perform a robust selective background updating procedure by considering the complement of these masks. Besides, the analysis of a strip of pixels surrounding each coarse-grain blob allows to infer information on light changes possibly occurring in the blob\´s vicinity. Although any algorithm can be used as the final fine-level detection, here we show how the approach applies to a particular algorithm we devised, based on a non-parametric statistical modelling of the camera noise.
Keywords :
computer vision; image sequences; statistical analysis; camera noise; change detectors; coarse-grain blob; coarse-level detection; coarse-to-fine strategy; computer vision; nonparametric statistical modelling; subsequent fine-level detection; Cameras; Change detection algorithms; Computer science; Detectors; Filters; Information analysis; Lighting; Robustness; Strips; Switches;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advanced Video and Signal Based Surveillance, 2005. AVSS 2005. IEEE Conference on
Print_ISBN :
0-7803-9385-6
Type :
conf
DOI :
10.1109/AVSS.2005.1577248
Filename :
1577248
Link To Document :
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