Evaluation of disparity maps
Ivan Cabezas, Maria Trujillo | 2014-03-28
A disparity map is the output of a stereo correspondence algorithm. It is estimated in an intermediate step of a
3D information recovery process, from two or more images. A performance assessment of stereo correspondence
algorithms may be addressed by a quantitative comparison of estimated disparity maps against ground-truth data.
This assessment requires of the use of a methodology, which involves several evaluation elements and methods.
Some elements and methods have been discussed with more attention than others in the literature. In the one hand,
the quantity of used images and their relation to the application domain are topics rising large debate. On the other
hand, there exist few publications on evaluation measures and error criteria. In practice, contradictory evaluation
results may be obtained if different error measures are used, even on a same test-bed. In this paper, an evaluation
methodology for stereo correspondence algorithms is presented. In contrast to conventional methodologies, it allows
an interactive selection of multiple evaluation elements and methods. Moreover, it is based on a formal definition of
error criteria based on set partitions. Experimental evaluation results showed that the proposed methodology allows
a better understanding and analysis of algorithms performance than the Middlebury methodology. Final remarks
highlights the relevance of discussing on the different elements and methods involved in an evaluation process.