Constraint-based Correspondence Matching for Stereo-based Interactive Robotic Massage Machine

Locating the 3D positions of the points on the human back is an essential issue in stereo-based interactive robotic back massage machines. In stereoscopic 3D localization, the 3D positions are determined from the corresponding image points captured by calibrated stereo cameras. However, detecting these corresponding points on the human back is highly challenging due to the smooth and texture-less characteristics of human skin. In the present study, this problem is resolved by means of a novel correspondences detection scheme designated as Correspondences from Epipolar geometry and Contours via Triangle barycentric coordinates (CECT). In the proposed approach, reliable correspondences are extracted from the edge contours of the human back by applying epipolar geometry, and these correspondences are then used to compute the correspondences of the featureless points within the edge contour using a triangle barycentric coordinate approach. The accuracy and robustness of the estimated correspondences are ensured by applying three geometric constraints, namely a similarity constraint, a shape constraint and an epipolar constraint. The performance of the proposed approach is demonstrated by means of a series of experiments involving 28 subjects and four different testing conditions. In addition, the accuracy of the proposed localization scheme is evaluated by comparing the estimated 3D positions with those obtained using the cun-based measurement method in Traditional Chinese Medicine (TCM).