Efficient moving object segmentation algorithm using background registration technique

By Shao-Yi Chien, Shyh-Yih Ma, Liang-Gee Chen. IEEE Trans. Circuits Syst. Video Technol., 2002

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Background Subtraction in Real Applications: Challenges, Current Models and Future Directions (2019, methodology): “(2002) [73] MPEG-4 (QCIF Format) Progressive Generation (CFD [1]) Progressive Maintenance CD [1] Intensity Post Processing/Shadow Detection”
Traditional and recent approaches in background modeling for foreground detection: An overview (2014, methodology): “So, video coding needs effective methods for object detection from static and dynamic environments [57][198].”
Unsupervised Detection and Tracking of Arbitrary Objects with Dependent Dirichlet Process Mixtures (2012, methodology): “These methods might be placed into a few broad categories: those that aim to distinguish the foreground regions of images from the background [33, 12, 65, 39], segment images into distinct regions to perform localization [35, 23, 56], track an object over a sequence of images (after its position has”
Video object tracking using adaptive Kalman filter (2006, background): “Or , in the environment of still background, [3,8] apply the diﬀerence information of two consecutive frames to extract the moving objects.”