Quick and accurate estimation of human 3D hand posture

Abstract

We propose a three-dimensional hand posture estimation system that can retrieve a hand posture image most similar to the input data from a non-multilayer database. Our system uses, at the first stage, coarse screening by the proportional information on the hand images, which roughly correspond to forearm rotation or bending of the thumb or four fingers; then, at the second stage, performs a detailed search for similarity for selected candidates. To describe forearm rotation, and wrist’s internal and external rotations, bending and stretching, no separate processes were used for estimating the corresponding joint angles. By estimating the sequential images of the finger shape using this method, we successfully realized a process involving a joint angle estimation error within two or three degrees, a processing time of approximately 80 fps or more, using only one Note PC and high-speed camera, even when the wrist was freely rotating. Since the image information and the joint angle information are paired in the database, as well as the wrist joint, the system can generate the imitative motions as those of the fingers and wrist of a human being with no time delay by means of a robot, by outputting the estimation results to the robot hand.