Background subtraction based on a Self-Adjusting MoG
暂无分享,去创建一个
[1] P. KaewTrakulPong,et al. An Improved Adaptive Background Mixture Model for Real-time Tracking with Shadow Detection , 2002 .
[2] Nebili Wafa,et al. A New Process for Selecting the Best Background Representatives based on GMM , 2018 .
[3] Du-Ming Tsai,et al. Independent Component Analysis-Based Background Subtraction for Indoor Surveillance , 2009, IEEE Transactions on Image Processing.
[4] Gerhard Rigoll,et al. A deep convolutional neural network for video sequence background subtraction , 2018, Pattern Recognit..
[5] Feng Qian,et al. Object kinematic model: A novel approach of adaptive background mixture models for video segmentation , 2010, 2010 8th World Congress on Intelligent Control and Automation.
[6] P. Wayne Power,et al. Understanding Background Mixture Models for Foreground Segmentation , 2002 .
[7] Xiaoqin Zhang,et al. Robust foreground segmentation based on two effective background models , 2008, MIR '08.
[8] Joseph L. Mundy,et al. Background Modeling Based on Subpixel Edges , 2007, 2007 IEEE International Conference on Image Processing.
[9] Larry S. Davis,et al. Non-parametric Model for Background Subtraction , 2000, ECCV.
[10] Serhat Selcuk Bucak,et al. Video Content Representation by Incremental Non-Negative Matrix Factorization , 2007, 2007 IEEE International Conference on Image Processing.
[11] A. B. Watkins,et al. A new classifier based on resource limited artificial immune systems , 2002, Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600).
[12] T. Charoenpong,et al. Adaptive background modeling from an image sequence by using K-Means clustering , 2010, ECTI-CON2010: The 2010 ECTI International Confernce on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology.
[13] Howida A. Shedeed,et al. A new technique for background modeling and subtraction for motion detection in real-time videos , 2010, 2010 IEEE International Conference on Image Processing.
[14] Thierry Bouwmans,et al. Fuzzy statistical modeling of dynamic backgrounds for moving object detection in infrared videos , 2009, 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops.
[15] Long Ang Lim,et al. Foreground Segmentation Using a Triplet Convolutional Neural Network for Multiscale Feature Encoding , 2018, Pattern Recognit. Lett..
[16] Stuart J. Russell,et al. Image Segmentation in Video Sequences: A Probabilistic Approach , 1997, UAI.
[17] Takeo Kanade,et al. A System for Video Surveillance and Monitoring , 2000 .
[18] Konrad Schindler,et al. Smooth Foreground-Background Segmentation for Video Processing , 2006, ACCV.
[19] Iqbal Gondal,et al. Automated multi-sensor color video fusion for nighttime video surveillance , 2010, The IEEE symposium on Computers and Communications.
[20] Xu Jian,et al. Background subtraction based on a combination of texture, color and intensity , 2008, 2008 9th International Conference on Signal Processing.
[21] Mubarak Shah,et al. Automatically Tuning Background Subtraction Parameters using Particle Swarm Optimization , 2007, 2007 IEEE International Conference on Multimedia and Expo.
[22] Viktor Öwall,et al. Background Segmentation Beyond RGB , 2006, ACCV.
[23] Herman Akdag,et al. Efficient local monitoring approach for the task of background subtraction , 2017, Eng. Appl. Artif. Intell..
[24] Alex Pentland,et al. Pfinder: Real-Time Tracking of the Human Body , 1997, IEEE Trans. Pattern Anal. Mach. Intell..
[25] Zhiming Luo,et al. Interactive deep learning method for segmenting moving objects , 2017, Pattern Recognit. Lett..
[26] Hongxun zhang,et al. Fusing Color and Texture Features for Background Model , 2006, FSKD.
[27] 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).
[28] Alex Pentland,et al. A Bayesian Computer Vision System for Modeling Human Interactions , 1999, IEEE Trans. Pattern Anal. Mach. Intell..
[29] Nikolaos F. Matsatsinis,et al. Self Adaptive background modeling for identifying persons' falls , 2010, 2010 Fifth International Workshop Semantic Media Adaptation and Personalization.
[30] Larry S. Davis,et al. W4: Real-Time Surveillance of People and Their Activities , 2000, IEEE Trans. Pattern Anal. Mach. Intell..
[31] Kentaro Toyama,et al. Wallflower: principles and practice of background maintenance , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.
[32] Marc Van Droogenbroeck,et al. Deep background subtraction with scene-specific convolutional neural networks , 2016, 2016 International Conference on Systems, Signals and Image Processing (IWSSIP).