A Background Model Estimation Algorithm Based on Analysis of Local Motion for Video Surveillance

Knowing the background model of a video scenario simplifies the problem of object segmentation and object tracking in the automated video surveillance applications. In this paper, a new algorithm for background model estimation was presented, which is useful in situations where an unobstructed view...

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Bibliographic Details
Published in2005 5th International Conference on Information Communications and Signal Processing pp. 700 - 704
Main Authors Si Luo, Li Zhang
Format Conference Proceeding
LanguageEnglish
Published IEEE 2005
Subjects
Algorithm design and analysis
automated visual surveillance
background estimation
background modeling
History
Information analysis
Information filtering
Information filters
Layout
Motion analysis
motion capture
Motion estimation
Object segmentation
Video surveillance
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ISBN9780780392830
0780392833
DOI10.1109/ICICS.2005.1689138

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Summary:Knowing the background model of a video scenario simplifies the problem of object segmentation and object tracking in the automated video surveillance applications. In this paper, a new algorithm for background model estimation was presented, which is useful in situations where an unobstructed view of the background is not always available. Discovering the true background interval in pixel's intensity history through local analysis of motion and spatial information, it avoids the problems of blending pixel values present in many current methods, such as mean filter and Kalman filter. Experimental results of applying our approach on a sequence of an indoor scene are provided to demonstrate the effectiveness of the proposed method
ISBN:9780780392830
0780392833
DOI:10.1109/ICICS.2005.1689138