Robust Foreground Object Segmentation via Adaptive Region-Based Background Modelling
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[1] Larry S. Davis,et al. Real-time foreground-background segmentation using codebook model , 2005, Real Time Imaging.
[2] Larry S. Davis,et al. Non-parametric Model for Background Subtraction , 2000, ECCV.
[3] Marko Heikkilä,et al. A texture-based method for modeling the background and detecting moving objects , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[4] Hitoshi Habe,et al. Background subtraction under varying illumination , 2006 .
[5] Lucia Maddalena,et al. A Self-Organizing Approach to Background Subtraction for Visual Surveillance Applications , 2008, IEEE Transactions on Image Processing.
[6] W. Eric L. Grimson,et al. Adaptive background mixture models for real-time tracking , 1999, Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149).
[7] Gary R. Bradski,et al. Learning OpenCV - computer vision with the OpenCV library: software that sees , 2008 .
[8] Brian C. Lovell,et al. Multi-Region Probabilistic Histograms for Robust and Scalable Identity Inference , 2009, ICB.
[9] Qi Tian,et al. Foreground object detection from videos containing complex background , 2003, MULTIMEDIA '03.
[10] Alex Pentland,et al. Pfinder: real-time tracking of the human body , 1996, Proceedings of the Second International Conference on Automatic Face and Gesture Recognition.
[11] Zoran Duric,et al. Using histograms to detect and track objects in color video , 2001, Proceedings 30th Applied Imagery Pattern Recognition Workshop (AIPR 2001). Analysis and Understanding of Time Varying Imagery.