Characterizing the Performance of Multiple-Image Point-Correspondence Algorithms Using Self-Consistency

Authors:
Yvan G. Leclerc;Quang-Tuan Luong;Pascal Fua
Affiliations:
-;-;-
Venue:
ICCV '99 Proceedings of the International Workshop on Vision Algorithms: Theory and Practice
Year:
1999

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Abstract

A new approach to characterizing the performance of point-correspondence algorithms is presented.Instead of relying on any "ground truth', it uses the self-consistency of the outputs of an algorithm independently applied to different sets of views of a static scene. It allows one to evaluate algorithms for a given class of scenes, as well as to estimate the accuracy of every element of the output of the algorithm for a given set of views. Experiments to demonstrate the usefulness of the methodology are presented.