Scheduled System Maintenance on May 29th, 2015:
IEEE Xplore will be upgraded between 11:00 AM and 10:00 PM EDT. During this time there may be intermittent impact on performance. We apologize for any inconvenience.
By Topic

Pose estimation and integration for complete 3D model reconstruction

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Park, S.-Y. ; Dept. of Electr. & Comput. Eng., State Univ. of New York, Stony Brook, NY, USA ; Subbarao, M.

An automatic 3D model reconstruction technique is presented to acquire complete 3D models of real objects. The technique is based on novel approaches to pose estimation and integration. Two different poses of an object are used because a single pose often hides some surfaces from a range sensor. The presence of hidden surfaces makes the 3D model reconstructed from any single pose a partial model. Two such partial 3D models are reconstructed for two different poses of the object using a multi-view 3D modeling technique. The two partial 3D models are then registered. Coarse registration is facilitated by a novel pose estimation technique between two models. The pose is estimated by matching a stable tangent plane (STP) of each pose model with the base tangent plane (BTP) which is invariant for a vision system. The partial models are then integrated to a complete 3D model based on voxel classification defined in multi-view integration. Texture mapping is done to obtain a photo-realistic reconstruction of the object.

Published in:

Applications of Computer Vision, 2002. (WACV 2002). Proceedings. Sixth IEEE Workshop on

Date of Conference: