Pose estimation of soccer players using multiple uncalibrated cameras

Fully automatic algorithm for estimating the 3D human pose from multiple uncalibrated cameras is presented. Unlike the state-of-the-art methods which use the estimated pose of previous frames to restrict the candidates of current frame, the proposed method uses the viewpoint of previous frame in order to obtain an accurate pose. This paper also introduces a method to incorporate pose estimation results of several cameras without using the calibration information. The algorithm employs a rich descriptor for matching purposes. The performance of the proposed method is evaluated on a soccer database which is captured by multiple cameras. The dataset of silhouettes, in which the related 3D skeleton poses are known, is also constructed. Experimental results show that the proposed algorithm has a high accuracy rate in estimation of 3D pose of soccer players.