MITSUBISHI ELECTRIC RESEARCH LABORATORIES http://www.merl.com Automatic Pose Estimation for Range Images on the GPU Marcel Germann, In Kyu Park Michael Breitenstein, Hanspeter Pfister TR2007-061 June 2007 Abstract Object pose (location and orientation) estimation is a common task in many computer vision applications. Although many methods exist, most algorithms need manual initialization and lack robustness to illumination variation, appearance change, and partial occlusions. We propose a fast method for automatic pose estimation without manual initialization based on shape matching of a 3D model to a range image of the scene. We developed a new error function to compare the input range image to pre-computed range maps of the 3D model. We use the tremendous data- parallel processing performance of modern graphics hardware to evaluate and minimize the error function on many range images in parallel. Our algorithm is simple and accurately estimates the pose of partially occluded objects in cluttered scenes in about one second. International Conference on 3-D digital Imaging and Modeling (3DIM) This work may not be copied or reproduced in whole or in part for any commercial purpose. Permission to copy in whole or in part without payment of fee is granted for nonprofit educational and research purposes provided that all such whole or partial copies include the following: a notice that such copying is by permission of Mitsubishi Electric Research Laboratories, Inc.; an acknowledgment of the authors and individual contributions to the work; and all applicable portions of the copyright notice. Copying, reproduction, or republishing for any other purpose shall require a license with payment of fee to Mitsubishi Electric Research Laboratories, Inc. All rights reserved. Copyright c Mitsubishi Electric Research Laboratories, Inc., 2007 201 Broadway, Cambridge, Massachusetts 02139