Volume 20 Issue 07 - Publication Date: 1 July 2001
Quantitative Evaluation of Matching Methods and Validity Measures for Stereo Vision
J. Banks Fraunhofer Institut Graphische Datenverarbeitung, P. Corke CSIRO Manufacturing Science and Technology
The authors present a qualitative and quantitative comparison of various similarity measures that form the kernel of common area-based stereo-matching systems. The authors compare classical difference and correlation measures as well as nonparametric measures based on the rank and census transforms for a number of outdoor images. For robotic applications, important considerations include robustness to image defects such as intensity variation and noise, the number of false matches, and computational complexity. In the absence of ground truth data, the authors compare the matching techniques based on the percentage of matches that pass the left-right consistency test. The authors also evaluate the discriminatory power of several match validity measures that are reported in the literature for eliminating false matches and for estimating match confidence. For guidance applications, it is essential to have an estimate of confidence in the three-dimensional points generated by stereo vision. Finally a new validity measure, the rank constraint, is introduced that is capable of resolving ambiguous matches for rank transform--based matching.
Multimedia Key
= Video = Data = Code = Image
Stereo pairs
Comparative results for different matching measures
Comparative results expressed as percentage match rate
Matching validity and confidence measures
Application of constraints to remove invalid matches
Ambiguous match scores
Rank-transform based matching with and without the rank constraint.
Results of rank error prediction and actual rank errors
Matching software (in C)
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