Integral approach to free-formed object modeling

This paper presents a new approach to free-formed 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 correspondences can be established among different views. The global resampling algorithm is based on the spherical attribute image (SAI) previously introduced in the context of object representation and recognition. Second, a weighted least square algorithm integrates resampled partial representations of multiple views, using the technique of principal component analysis with missing data (PCAMD). Experiments using real range images show that our approach is robust against noise and mismatch and generates accurate object models.