Stereo vision methods: from development to the evaluation of disparity maps

Abstract

The challenge in building disparity maps is to determine the best method to calculate consistency among points and use it to approximate the differences between the views. Fortunately, the number of methods to construct disparity maps have increased in the last years. On the other hand, a lot of work needs to be done to evaluate these methods by using different arguments. Besides, it is not clear enough how to build stereo vision algorithms with concepts as reuse and scalability. Thus, we propose a software design architecture to be applied in stereo vision systems. Furthermore, we have implemented disparity methods to perform an evaluation which objective was to determine what cost function better fits in each method analyzed. We conclude that MLMH method with SSD cost function is a good choice to be applied in the scenes we have selected, according to the statistical analysis performed.

Publication
In Proceedings of 23th Brazilian Workshop on Computer Vision (WVC)
Gabriel Vieira
Gabriel Vieira
PhD Student
and former Master’s Student

Fabrizzio Soares is bla bla bla.

Fabrizzio Soares
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.

Naiane Sousa
Naiane Sousa
Master’s Student

Fabrizzio Soares is bla bla bla.

Rafael Parreira
Rafael Parreira
Master’s Student

Fabrizzio Soares is bla bla bla.

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