By Topic

Multi-scale feature extraction for 3d surface registration using local shape variation

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)
Huy Tho Ho ; Sensor Signal Process. Group, Univ. of Adelaide, Adelaide, SA ; Gibbins, D.

This paper describes a method for extracting salient local features from 3D models using shape variation which has application to 3D surface registration. In the proposed technique, the surface shape at a point is specified by a quantitative measure known as the shape index. It is invariant to rigid transformations such as translation and rotation. The shape index at a point is calculated at multiple scales by fitting a surface to the local neighbourhoods of different sizes. The local surface variation is then measured by calculating the variation of the shape index of every point in the neighbourhood. Points corresponding to local maxima of surface variation are selected as suitable features. Experimental results of applying the proposed feature extraction method on a variety of 3D models are shown to evaluate the effectiveness and robustness of our approach.

Published in:

Image and Vision Computing New Zealand, 2008. IVCNZ 2008. 23rd International Conference

Date of Conference:

26-28 Nov. 2008