ABSTRACT
Most of the video coding applications could not tolerate inaccurate video/object segmentations and expensive computational complexity incurred by segmentation algorithms. Most common frame in a scene McFIS can be used for video compression as a reference frame for referencing static and uncovered areas because of its capability of capturing a whole cycle of repetitive motion, exposing uncovered background, noninteger pixel displacement, or lighting change. Encoding the moving entities is thus the primary focus of any video coding technology to construct high-quality video within the constrained bit rates. Traditional dynamic background modeling techniques primarily focus on object detection; thus, it has less concern about real-time processing as well as rate-distortion performance optimization in video compression. The preprocessing approach for video coding is different from the existing paradigms by exploring the information redundancy in a fuller extent. Computer vision tool such as dynamic background modeling, that is, McFIS can be used for different purposes of video coding.
