Motion-based background subtraction using adaptive kernel density estimation
暂无分享,去创建一个
[1] L. Breiman,et al. Variable Kernel Estimates of Multivariate Densities , 1977 .
[2] Berthold K. P. Horn,et al. Determining Optical Flow , 1981, Other Conferences.
[3] Ian Abramson. On Bandwidth Variation in Kernel Estimates-A Square Root Law , 1982 .
[4] Jitendra Malik,et al. Robust Multiple Car Tracking with Occlusion Reasoning , 1994, ECCV.
[5] Matthew P. Wand,et al. Kernel Smoothing , 1995 .
[6] Lucia Ballerini,et al. Time-Varying Image Processing and Moving Object Recognition , 1997 .
[7] Alex Pentland,et al. Pfinder: Real-Time Tracking of the Human Body , 1997, IEEE Trans. Pattern Anal. Mach. Intell..
[8] Stuart J. Russell,et al. Image Segmentation in Video Sequences: A Probabilistic Approach , 1997, UAI.
[9] W. Eric L. Grimson,et al. Using adaptive tracking to classify and monitor activities in a site , 1998, Proceedings. 1998 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No.98CB36231).
[10] Eero P. Simoncelli. Bayesian multi-scale differential optical flow , 1999 .
[11] Kentaro Toyama,et al. Wallflower: principles and practice of background maintenance , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.
[12] Alex Pentland,et al. A Bayesian Computer Vision System for Modeling Human Interactions , 1999, IEEE Trans. Pattern Anal. Mach. Intell..
[13] Heinrich Niemann,et al. Statistical modeling and performance characterization of a real-time dual camera surveillance system , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).
[14] Larry S. Davis,et al. Non-parametric Model for Background Subtraction , 2000, ECCV.
[15] Xiang Gao,et al. Error analysis of background adaption , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).
[16] Haifeng Chen,et al. Robust Computer Vision through Kernel Density Estimation , 2002, ECCV.
[17] Michael Harville,et al. A Framework for High-Level Feedback to Adaptive, Per-Pixel, Mixture-of-Gaussian Background Models , 2002, ECCV.
[18] Mubarak Shah,et al. A hierarchical approach to robust background subtraction using color and gradient information , 2002, Workshop on Motion and Video Computing, 2002. Proceedings..
[19] Dorin Comaniciu,et al. Nonparametric information fusion for motion estimation , 2003, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings..
[20] Nikos Paragios,et al. Background modeling and subtraction of dynamic scenes , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.
[21] Stan Sclaroff,et al. Segmenting foreground objects from a dynamic textured background via a robust Kalman filter , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.
[22] P. Anandan,et al. A computational framework and an algorithm for the measurement of visual motion , 1987, International Journal of Computer Vision.
[23] Stefano Soatto,et al. Dynamic Textures , 2003, International Journal of Computer Vision.
[24] David J. Fleet,et al. Performance of optical flow techniques , 1994, International Journal of Computer Vision.