Measuring the Self-Consistency of Stereo Algorithms

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 di erent 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.

• Type: Conference
• Year: 2000
• Where: ECCV
• Authors: Yvan G. Leclerc, Quang-Tuan Luong, Pascal Fua
• Keywords: Algorithm, Computer Vision, ECCV 2000, Point-correspondence Algorithms, \ground Truth