TY - GEN

T1 - A robust point matching algorithm for non-rigid registration using the Cauchy-Schwarz divergence

AU - Hasanbelliu, Erion

AU - Giraldo, Luis Sanchez

AU - Príncipe, José C.

PY - 2011

Y1 - 2011

N2 - In this paper, we describe an algorithm that provides both rigid and non-rigid point-set registration. The point sets are represented as probability density functions and the registration problem is treated as distribution alignment. Using the PDFs instead of the points provides a more robust way of dealing with outliers and noise, and it mitigates the need to establish a correspondence between the points in the two sets. The algorithm operates on the distance between the two PDFs to recover the spatial transformation function needed to register the two point sets. The distance measure used is the Cauchy-Schwarz divergence. The algorithm is robust to noise and outliers, and performswell in varying degrees of transformations and noise.

AB - In this paper, we describe an algorithm that provides both rigid and non-rigid point-set registration. The point sets are represented as probability density functions and the registration problem is treated as distribution alignment. Using the PDFs instead of the points provides a more robust way of dealing with outliers and noise, and it mitigates the need to establish a correspondence between the points in the two sets. The algorithm operates on the distance between the two PDFs to recover the spatial transformation function needed to register the two point sets. The distance measure used is the Cauchy-Schwarz divergence. The algorithm is robust to noise and outliers, and performswell in varying degrees of transformations and noise.

KW - Cauchy-Schwarz divergence

KW - information theoretic learning

KW - non-rigid registration

KW - shape matching

UR - http://www.scopus.com/inward/record.url?scp=82455198834&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=82455198834&partnerID=8YFLogxK

U2 - 10.1109/MLSP.2011.6064593

DO - 10.1109/MLSP.2011.6064593

M3 - Conference contribution

AN - SCOPUS:82455198834

SN - 9781457716232

T3 - IEEE International Workshop on Machine Learning for Signal Processing

BT - 2011 IEEE International Workshop on Machine Learning for Signal Processing - Proceedings of MLSP 2011

T2 - 21st IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2011

Y2 - 18 September 2011 through 21 September 2011

ER -