3D human tracking in a top view using depth information recorded by the Xtion Pro-Live camera

Abstract

This paper addresses the problem of the tracking of 3D human body pose from depth image sequences given by a Xtion Pro-Live camera. Human body poses could be estimated through model fitting using dense correspondences between depth data and an articulated human model. Although, most of the time for the video surveillance, the camera is placed above the persons, all the tracking methods use the front view. Indeed the human shape is more discriminative in this view. We propose a new model to be fitted to the top view in a particle filter framework for a real-time markerless tracking. The model is composed of two parts: a 2D model providing the human localization and a 3D model providing its pose. There are few wrong estimations and they are efficiently detected by a confidence measure.... © 2013 Springer-Verlag.