Abstract
In this work, we propose a disparity refinement method to be applied in stereo matching algorithms. It consists of a segmentation process, statistical analysis of grouping areas and a support weighted function to find unknown disparities. We investigate the behavior of this method by comparing it with other post-processing techniques, as the left to right consistency-check. By comparing some of the most common refinement techniques, the experimental results show that or method achieved the lowest erros in non-weighted functions. Furthermore, through a qualitative evaluation, it is possible to note that our method reaches significant results, close to the ground truth maps.
Fabrizzio Soares
Associate Professor and CS Chair
Fabrizzio Soares is a professor of Computer Science, Information Systems and Software Engineering at INF/UFG. His research interests include Computer Vision, Human Computer Interaction, Machine Learning and Programming topics. He is the leader of the Pixellab group, which develops solutions for accesibilty, Precision Agriculture, and Interactive Systems.
