A primal-dual framework for real-time dense RGB-D scene flow
| Autor: | Mohamed Souiai, Javier Gonzalez-Jimenez, Mariano Jaimez, Daniel Cremers |
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| Rok vydání: | 2015 |
| Předmět: |
Automatización
business.industry Computer science ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Primal-dual Image plane Frame rate Regularization (mathematics) RGBD camera Primal dual Variational methods Computer Science::Computer Vision and Pattern Recognition RGB color model Scene flow Computer vision Artificial intelligence business ComputingMethodologies_COMPUTERGRAPHICS |
| Zdroj: | ICRA RIUMA. Repositorio Institucional de la Universidad de Málaga instname |
| Popis: | This paper presents the first method to compute dense scene flow in real-time for RGB-D cameras. It is based on a variational formulation where brightness constancy and geometric consistency are imposed. Accounting for the depth data provided by RGB-D cameras, regularization of the flow field is imposed on the 3D surface (or set of surfaces) of the observed scene instead of on the image plane, leading to more geometrically consistent results. The minimization problem is efficiently solved by a primal-dual algorithm which is implemented on a GPU, achieving a previously unseen temporal performance. Several tests have been conducted to compare our approach with a state-of-the-art work (RGB-D flow) where quantitative and qualitative results are evaluated. Moreover, an additional set of experiments have been carried out to show the applicability of our work to estimate motion in realtime. Results demonstrate the accuracy of our approach, which outperforms the RGB-D flow, and which is able to estimate heterogeneous and non-rigid motions at a high frame rate. Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech. Research supported by the Spanish Government under project DPI1011-25483 and the Spanish grant program FPI-MICINN 2012. |
| Databáze: | OpenAIRE |
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