Spectral Shape Decomposition by Using a Constrained NMF Algorithm

In this paper, the shape decomposition problem is addressed as a solution of an appropriately constrained Nonnegative Matrix Factorization Problem (NMF). Inspired from an idealization of the visibility matrix having a block diagonal form, special requirements while formulating the NMF problem are taken into account. Starting from a contaminated observation matrix, the objective is to reveal its low rank almost block diagonal form. Although the proposed technique is applied to shapes on the MPEG7 database, it can be extended to 3D objects. The preliminary results we have obtained are very promising.

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