[ACM Press the 2018 2nd International Conference - Barcelona, Spain (2018.08.03-2018.08.05)] Proceedings of the 2018 2nd International Conference on Cloud and Big Data Computing - ICCBDC'18 - Optical Flow Based Pose Estimation

摘要： In this paper, we present a new variant of ICP (iterative closest point) algorithm based on optical flow for finding better 3D point correspondence and computing six-degrees of freedom (6-DOF) pose of the rigid objects. Our approach integrates optical flow algorithm to ICP method, and proposed method gets advantage of higher resolution of the RGB sensor and depth information of the depth sensor. Fusing color and depth sensors improves pose estimation results. We set ground truth with Vicon motion tracker system. And, our approach is tested on a rigid object and compared to ICP method. Results have shown that optical flow and ICP method computes better rigid object pose estimation and lower error against ICP based pose estimation with only depth positions.