We propose a simple, inexpensive, portable and real-time image processing s
ystem for kinematic analysis of human gait. We view this as a feature based
multi-target tracking problem. Here we track the artificially induced feat
ures appearing in the image sequence due to the non-impeding contrast marke
rs attached at different anatomical landmarks of the subject under analysis
. This paper describes a real-time algorithm for detecting and tracking the
feature points simultaneously. By applying a Kalman filter, we recursively
predict the tentative features location and retain the predicted point in
case of occlusion. A path coherence score is used for disambiguation along
with tracking for establishing feature correspondences. Experimentations on
normal and pathological subjects in different gait was performed and resul
ts illustrate the efficacy of the algorithm. (C) 2000 Academic Press.