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Author Germann, Marcel ♦ Park, In Kyu ♦ Breitenstein, Michael D. ♦ Pfister, Hanspeter
Source CiteSeerX
Content type Text
File Format PDF
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Error Function ♦ Range Image ♦ Tremendous Dataparallel ♦ Many Range Image ♦ Many Method ♦ Input Range Image ♦ Shape Matching ♦ Lack Robustness ♦ Illumination Variation ♦ Automatic Pose Estimation ♦ Manual Initialization ♦ Fast Method ♦ Modern Graphic Hardware ♦ Pre-computed Range Map ♦ Object Pose ♦ Common Task ♦ New Error Function ♦ Appearance Change ♦ Cluttered Scene ♦ Many Computer Vision Application ♦ Partial Occlusion
Description 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 dataparallel 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. 1.
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research
Education Level UG and PG ♦ Career/Technical Study
Learning Resource Type Article
Publisher Date 2007-01-01
Publisher Institution In International Conference on 3-D Digital Imaging and Modeling