Recognizing jump patterns with physics-based validation in human moving trajectory

Abstract

This paper presents an approach to recognize jump patterns in human moving trajectory, differentiating jump tracks from planar moving tracks. Since human moving trajectory is one of the most informative representations for content understanding and event detection, trajectory-based video analysis has been gaining popularity. However, a jump action typically leads to violent change in human moving trajectory, since the person suddenly leaves the original plane on which he/she has been moving. The abnormal tracks of the trajectory would influence the performance of trajectory-based video analysis. Hence, differentiating jump tracks from planar moving tracks is of vital importance, not to mention that jump actions typically imply significant events, especially in sports games. In this paper, volleyball videos are used as case study to demonstrate the effectiveness of our proposed jump pattern recognition approach. We derive player trajectory by head tracking, analyze the movement of each player, and recognize potential jump tracks in player trajectories based on two important characteristics: (1) jumps cause pulse-like tracks in the trajectory and (2) the extensions of such tracks go through the vanishing point of vertical lines in the scenes. Finally, the jump positions/heights are estimated, in addition to the planar moving trajectory of each player on the court ground. The experiments show that satisfactory results can be obtained with the proposed recognition scheme. (C) 2013 Elsevier Inc. All rights reserved.