Maximally stable curvature regions for 3D hand tracking

Abstract

Fast and robust hand detections and tracking is in increasing demand from areas such as natural Human Robot interaction(HRI) and surveillance systems. Previous works always use skin color or contour model to detection hand. However, they always fail for hands always exhibits drastic appearance change due to illumination change, non-rigid nature and hands are hard to discriminate from clutter background. Actually, the hand region has a specific nature that its curvature is relatively higher than other body parts and keeps stable whatever its poses and locations are, but none of pervious works exploit this nature for hand detection. In this work, a novel algorithm MSCR (Maximally Stable Curvature Regions) based on curvature nature to detect hands. It does not require manually initialization in the first frame, the hands are located by MSCR and skin color detector in the global image. 3D optical flow integrated Kalman Filter works to estimate the next location for local detector. Extensive experiments demonstrate that robust 3D tracking of hand articulations can be achieved in real-time with accurate results.