A Non-linear Quantitative Evaluation Approach for Disparity Estimation - Pareto Dominance Applied in Stereo Vision

Performance evaluation of vision algorithms is a necessary step during a research process. It may supports inter and intra technique comparisons. A fair evaluation process requires of a methodology. Disparity estimation evaluation involves multiple aspects. However, conventional approaches rely on the use of a single value as an indicator of comparative performance. In this paper a non-linear quantitative evaluation approach for disparity estimation is introduced. It is supported by Pareto dominance and Pareto optimal set concepts. The proposed approach allows different evaluation scenarios, and offers advantages over traditional evaluation approaches. The experimental validation is conducted using ground truth data. Innovative results obtained by applying the proposed approach are presented and discussed.