Human Segmentation from Video in Indoor Environments Using Fused Color and Texture Features

Abstract--A requirement for robust human activity analysis from video in complex and dynamic environments involves the reliable segmentation of individuals. This paper describes a system that has been built to segment moving people in video using the strengths of both color and texture features. In addition, a new algorithm was developed for the detection and removal of shadows from change detection images. To preserve the privacy of the individual, the output of this system is a binary map segmentation that distinguishes the individual’s silhouette from his or her background.

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