Bi-directional labeled point matching

Authors:
Roshni Bhagalia;James V. Miller;Arunabha Roy
Affiliations:
GE Global Research, Niskayuna;GE Global Research, Niskayuna;GE Global Research, Bangalore, India
Venue:
ISBI'10 Proceedings of the 2010 IEEE international conference on Biomedical imaging: from nano to Macro
Year:
2010

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Abstract

Robust point matching (RPM) simultaneously estimates correspondences and non-rigid warps between unstructured point-sets. While RPM is robust to outliers in the target (fixed) point-set, its performance degrades when the template (moving) point-set contains outliers. Additionally, RPM does not utilize information about the topological structure or group memberships of the data it is matching. Bi-directional Labeled Point Matching (BLPM) extends the RPM objective function by introducing (i) Bi-Directionality (BD) and (ii) a Label Entropy (LE) term. BD aids in outlier rejection in both point-sets and LE discourages mappings that transform points within a single group in one point-set onto points from multiple distinct groups in the other pointset. The resulting BLPM algorithm translates into simple modifications to the standard RPM update rules.