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IPMI
2009
Springer

Generalized L2-Divergence and Its Application to Shape Alignment

12 years 8 months ago
Generalized L2-Divergence and Its Application to Shape Alignment
This paper proposes a novel and robust approach to the groupwise point-sets registration problem in the presence of large amounts of noise and outliers. Each of the point sets is represented by a mixture of Gaussians and the point-sets registration is treated as a problem of aligning the multiple mixtures. We develop a novel divergence measure which is defined between any arbitrary number of probability distributions based on L2 distance, and we call this new divergence measure ”Generalized L2divergence”. We derive a closed-form expression for the Generalized-L2 divergence between multiple Gaussian mixtures, which in turn leads to a computationally efficient registration algorithm. This new algorithm has an intuitive interpretation, is simple to implement and exhibits inherent statistical robustness. Experimental results indicate that our algorithm achieves very good performance in terms of both robustness and accuracy.
Fei Wang, Baba C. Vemuri, Tanveer Fathima Syeda-Ma
Added 20 May 2010
Updated 20 May 2010
Type Conference
Year 2009
Where IPMI
Authors Fei Wang, Baba C. Vemuri, Tanveer Fathima Syeda-Mahmood
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