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Conference papers
Disparity and normal estimation through alternating maximization
Abstract : In this paper, we propose an algorithm that recovers binocular disparities in accordance with the surface properties of the scene under consideration. To do so, we estimate the disparity as well as the normals in the disparity space, by setting the two tasks in a unified framework. A novel joint probabilistic model is defined through two random fields to favor both intra field (within neighboring disparities and neighboring normals) and inter field (between disparities and normals) consistency. Geometric contextual information is introduced in the models for both normals and disparities, which is optimized using an appropriate alternating maximization procedure. We illustrate the performance of our approach on synthetic and real data.
https://hal.inria.fr/inria-00517864
Contributor : Elise Arnaud Connect in order to contact the contributor
Submitted on : Wednesday, September 15, 2010 - 5:19:36 PM
Last modification on : Monday, February 7, 2022 - 1:54:01 PM
Long-term archiving on: : Friday, December 2, 2016 - 1:56:40 AM
Contributor : Elise Arnaud Connect in order to contact the contributor
Submitted on : Wednesday, September 15, 2010 - 5:19:36 PM
Last modification on : Monday, February 7, 2022 - 1:54:01 PM
Long-term archiving on: : Friday, December 2, 2016 - 1:56:40 AM