An Integral Approach to Free-Form Object Modeling

Authors:
Heung-Yeung Shum;Martial Hebert;Katsushi Ikeuchi;Ray Reddy
Affiliations:
Microsoft Corporation, Redmond, WA;Carnegie Mellon Univ., Pittsburgh, PA;Univ. of Tokyo, Tokyo, Japan;Carnegie Mellon Univ., Pittsburgh, PA
Venue:
IEEE Transactions on Pattern Analysis and Machine Intelligence
Year:
1997

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Abstract

This paper presents a new approach to free-form object modeling from multiple range images. In most conventional approaches, successive views are registered sequentially. In contrast to the sequential approaches, we propose an integral approach which reconstructs statistically optimal object models by simultaneously aggregating all data from multiple views into a weighted least-squares (WLS) formulation. The integral approach has two components. First, a global resampling algorithm constructs partial representations of the object from individual views, so that correspondence can be established among different views. Second, a weighted least-squares algorithm integrates resampled partial representations of multiple views, using the techniques of principal component analysis with missing data (PCAMD). Experiments show that our approach is robust against noise and mismatch.