Multiple object tracking in soccer videos using topographic surface analysis

Abstract

Multiple object tracking is still a challenging problem in computer vision even though there have been several attempts lately to resolve the tracking problem in the framework of deep neural networks. In this paper, a novel method for multiple object tracking in soccer videos, which often contain complicated interactions between players with severe occlusions, is introduced. To do this, we propose to interpret the extracted foreground regions in a given frame as the topographic surface. This gives a great help to reliably chase target players by accurately providing the boundary lines of each object even with occlusions. Color similarity and spatial proximity are subsequently employed to refine the estimated position of target players for continuous tracking over whole video sequences. Experimental results on various soccer videos, which are taken of the actual games with the wide-angle camera, demonstrate that the proposed method is effective for tracking multiple players in the dynamic scene of the soccer video.