A 3-D marker-free system for the analysis of movement disabilities--an application to the legs

The aim of this paper is to describe an approach allowing the analysis of human motion in three-dimensional (3-D) space. The system that we developed is composed of three charge-coupled-device cameras that capture synchronized image sequences of a human body in motion without the use of markers. Characteristic points belonging to the boundaries of the body in motion are first extracted from the initial images. Two-dimensional superquadrics are then adjusted on these points by a fuzzy clustering process. After that, the position of a 3-D model based on a set of articulated superquadrics, each of them describing a part of the human body, is reconstructed. An optical flow process allows the prediction of the position of the model from its position at the previous time, and gives initial values for the fuzzy classification. The results that we present concern more specifically the analysis of movement disabilities of a human leg during gait. They are improved by using articulation-based constraints. The methodology can be used in human motion analysis for clinical applications.