Design and Implementation of a Real-Time RGB-D Visual Pose Estimation Algorithm

• Main Authors: Chia-Hsien Lu, 盧家賢
• Other Authors: Chi-Yi Tsai
• Format: Others
• Language: zh-TW
• Published: 2016
• Online Access: http://ndltd.ncl.edu.tw/handle/01586409556918175094

碩士 === 淡江大學 === 電機工程學系碩士班 === 104 === Visual pose estimation technique, which estimates three-dimensional (3D) motion information of a camera system from changes of image features between adjacent frames, is an important core technology in vision-based robot localization systems. However, this technique usually is computationally expensive and is very sensitive to feature matching outliers. To address these technical problems, this thesis presents a RGB-D mapping algorithm that uses RGB-D visual sensing information to improve accuracy and robustness of six Degree-of-Freedom (6 DoF) motion estimation of the camera system. The proposed algorithm estimates the optimal 6 DoF posture information of the camera from the 3D feature matches between two RGB-D frames via a nonlinear optimization process. To improve the computational efficiency of the system, this thesis also derives Jacobian matrix associated with the cost function to reduce computational complexity of the optimization process, thereby enhancing overall system processing speed. Moreover, the proposed algorithm is combined with M-estimators to improve the robustness of the system against the influence of matching outliers. In the experiments, the performance of the proposed algorithm adopting three different types of M-estimators was studied by using RGB-D images corrected in our laboratory and provided on Computer Vision Group website [1].