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Pose Recognition for Tracker Initialization Using 3D Models

<p>In this thesis it is examined whether the pose of an object can be determined by a system trained with a synthetic 3D model of said object. A number of variations of methods using P-channel representation are examined. Reference images are rendered from the 3D model, features, such as gradient orientation and color information are extracted and encoded into P-channels. The P-channel representation is then used to estimate an overlapping channel representation, using B<sub>1</sub>-spline functions, to estimate a density function for the feature set. Experiments were conducted with this representation as well as the raw P-channel representation in conjunction with a number of distance measures and estimation methods.</p><p>It is shown that, with correct preprocessing and choice of parameters, the pose can be detected with some accuracy and, if not in real-time, fast enough to be useful in a tracker initialization scenario. It is also concluded that the success rate of the estimation depends heavily on the nature of the object.</p>

Identiferoai:union.ndltd.org:UPSALLA/oai:DiVA.org:liu-11080
Date January 2008
CreatorsBerg, Martin
PublisherLinköping University, Department of Electrical Engineering, Institutionen för systemteknik
Source SetsDiVA Archive at Upsalla University
LanguageEnglish
Detected LanguageEnglish
TypeStudent thesis, text

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