3D Objects Face Clustering using Unsupervised Mean Shift [article]

M. Farenzena, M. Cristani, U. Castellani, A. Fusiello
2007 Smart Tools and Applications in Graphics  
In this paper, a novel approach to face clustering is proposed. The aim is the completely unsupervised extraction of planes in a polygonal a mesh, obtained from a 3D reconstruction process. In this context, 3D coordinates points are inevitably affected by error, therefore resiliency is a primal concern in the analysis. The method is based on the Mean Shift clustering paradigm, devoted to separating modes of a multimodal non-parametric density, by using a kernel-based technique. A critical
more » ... ter, the kernel bandwidth size, is here automatically detected by following a well-accepted partition stability criterion. Experimental and comparative results on synthetic and real data validate the approach.
doi:10.2312/localchapterevents/italchap/italianchapconf2007/039-043 dblp:conf/egItaly/FarenzenaCCF07 fatcat:mzwlul3r4fg3nmt6pnzld572hy