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

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2 Author(s)
Huy Tho Ho ; Sensor Signal Processing Group, School of Electrical and Electronic Engineering, The University of Adelaide, Australia ; Danny Gibbins

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:

2008 23rd International Conference Image and Vision Computing New Zealand

Date of Conference:

26-28 Nov. 2008