Title :
New developments on geometric hashing for curve matching
Author :
Guéziec, Andre ; Ayache, Nicholas
Author_Institution :
INRIA, Sophia-Antipolis, France
Abstract :
The problem of fast rigid matching of 3D curves with subvoxel precision is addressed. More invariant parameters are used, and new hash tables are implemented in order to process larger and more complex sets of data curves. There exists a Bayesian theory of geometric hashing that explains why local minima are not really a problem. The more likely transformation always wins. It is also possible to predict the uncertainty on the match with the help of the Kalman filter, and compare it with real measures
Keywords :
Bayes methods; Kalman filters; differential geometry; file organisation; image matching; invariance; splines (mathematics); 3D curves; Bayesian theory; Kalman filter; curve matching; data curves; fast rigid matching; geometric hashing; hash tables; local minima; subvoxel precision; uncertainty; Bayesian methods; Q measurement; Shape; Skull; Spline; Surgery;
Conference_Titel :
Computer Vision and Pattern Recognition, 1993. Proceedings CVPR '93., 1993 IEEE Computer Society Conference on
Conference_Location :
New York, NY
Print_ISBN :
0-8186-3880-X
DOI :
10.1109/CVPR.1993.341020
