By Topic

A novel modeling algorithm for shape recovery of unknown topology

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
$33 $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)
Y. Duan ; State Univ. of New York, Stony Brook, NY, USA ; H. Qin

This paper presents a novel modeling algorithm that is capable of simultaneously recovering correct shape geometry as well as its unknown topology from arbitrarily complicated datasets. Our algorithm starts from a simple seed model (of genus zero) that can be arbitrarily initiated by users within any dataset. The deformable behavior of our model is governed by a locally defined objective function associated with each vertex of the model. Through the numerical computation of function optimization, our algorithm can adaptively subdivide the model geometry, automatically detect self-collision of the model, properly modify its topology (because of the occurrence of self-collision), continuously evolve the model towards the object boundary, and reduce fitting error and improve fitting quality via global subdivision. Commonly used mesh optimization techniques are employed throughout the geometric deformation and topological variation in order to ensure the model both locally smooth and globally well conditioned. We have applied our algorithm to various real/synthetic range data as well as volumetric image data in order to empirically verify and validate its usefulness. Based on our experiments, the new modeling algorithm proves to be very powerful and extremely valuable for shape recovery in computer vision, reverse engineering in computer graphics, and iso-surface extraction in visualization

Published in:

Computer Vision, 2001. ICCV 2001. Proceedings. Eighth IEEE International Conference on  (Volume:1 )

Date of Conference: