A robust markerless vision-based human gait analysis system

In this paper, a novel robust markerless image processing system capable of extracting gait features which can be used for gait analysis is presented. The presented system can deal with images of persons captured in natural indoor scenes. The system's robustness against external influences and different person appearance is achieved by employing the idea of improving the image processing robustness by including feedback control at the image segmentation level. The effectiveness of the proposed system is demonstrated by the comparison of gait features, namely knee angles, extracted automatically with the features directly measured using a goniometer. Also a small database is created to extract the gait pattern of healthy subjects. The obtained data is compared to data from medical literature and is also compared to data obtained from persons having a pathological gait.