Making Background Subtraction Robust to Sudden Illumination Changes

Author:

Pilet Julien,Strecha Christoph,Fua Pascal

Publisher

Springer Berlin Heidelberg

Reference16 articles.

1. Zivkovic, Z., van der Heijden, F.: Efficient adaptive density estimation per image pixel for the task of background subtraction. Pattern Recognition Letters 27(7), 773–780 (2006)

2. Wren, C., Azarbayejani, A., Darrell, T., Pentland, A.: Pfinder: Real-time tracking of the human body. In: Photonics East, SPIE, vol. 2615 (1995)

3. Friedman, N., Russell, S.: Image segmentation in video sequences: A probabilistic approach. In: Annual Conference on Uncertainty in Artificial Intelligence, pp. 175–181 (1997)

4. Stauffer, C., Grimson, W.: Adaptive background mixture models for real-time tracking. In: CVPR, pp. 246–252 (1999)

5. Bishop, C.: Pattern Recognition and Machine Learning. Springer, Heidelberg (2006)

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