Silhouette extraction from human gait images sequence using cosegmentation

摘要

Gait based human identification is very useful for automatic person recognize through visual surveillance and has attracted more and more researchers. A key step in gait based human identification is to extract human silhouette from images sequence. Current silhouette extraction methods are mainly based on simple color subtraction. These methods have a very poor performance when the color of some body parts is similar to the background. In this paper a cosegmentation based human silhouette extraction method is proposed. Cosegmentation is typically defined as the task of jointly segmenting "something similar" in a given set of images. We can divide the human gait images sequence into several step cycles and every step cycle consist of 10-15 frames. The frames in human gait images sequence have following similarity: every frame is similar to the next or previous frame; every frame is similar to the corresponding frame in the next or previous step cycle; every pixel can find similar pixel in other frames. The progress of cosegmentation based human silhouette extraction can be described as follows: Initially only points which have high contrast to background are used as foreground kernel points, the points in the background are used as background kernel points, then points similar to foreground points will be added to foreground points set and the points similar to background points will be added to background points set. The definition of the similarity consider the context of the point. Experimental result shows that our method has a better performance comparing to traditional human silhouette extraction methods.