In this paper we propose an adaptive background estimation algorithm for outdoor video surveillance system. In order to enhance the adaptation to the slow illumination changes and variant input noise in long-term running, an improved Kalman filtering model based on local-region is discussed to dynamically estimate a background image, in which the parameters are predicted by a RLS adaptive filter accurately. The experiment results on real-world image sequences show that the algorithm performs robustly and effectively.
Adaptive background estimation for real-time traffic monitoring
2001-01-01
569476 byte
Conference paper
Electronic Resource
English
Adaptive Background Estimation for Real-Time Traffic Monitoring
British Library Conference Proceedings | 2001
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