Object-Wise Multilayer Background Ordering for Public Area Surveillance
AVSS '09 Proceedings of the 2009 Sixth IEEE International Conference on Advanced Video and Signal Based Surveillance
An efficient and robust sequential algorithm for background estimation in video surveillance
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Patch-based background initialization in heavily cluttered video
IEEE Transactions on Image Processing
Background estimation using graph cuts and inpainting
Proceedings of Graphics Interface 2010
Journal on Image and Video Processing - Special issue on advanced video-based surveillance
Background subtraction for automated multisensor surveillance: a comprehensive review
EURASIP Journal on Advances in Signal Processing - Special issue on advanced image processing for defense and security applications
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part III
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In this paper we propose a technique to robustly estimate the background in a cluttered sequence, i.e., a sequence where occluding objects persist in the same position for a considerable portion of time. As pixel-level heuristic are not sufficient in this case, we introduce spatial support. First the sequence is subdivided in patches that are clustered along the time-line in order to narrow down the number of background candidates. Then the background is grown incrementally by selecting at each step the best continuation of the current background, according to the principles of visual grouping. The method rests on sound principles in all its stages, and only few, intelligible parameters are needed. Experiments with real sequences illustrate the approach.