2026-06-06T04:18:51Zhttps://riuma.uma.es/rest/oai/request

oai:riuma.uma.es:10630/99662026-02-03T11:50:42Zcom_10630_2254col_10630_37959

00925njm 22002777a 4500 dc Jaimez, Mariano author Souiai, Mohamed author González-Jiménez, Antonio Javier author Cremers, Daniel author 2015-05 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. M. Jaimez, M. Souiai, J. Gonzalez-Jimenez, D. Cremers, "A Primal-Dual Framework for Real-Time Dense RGB-D Scene Flow", IEEE Int. Conference on Robotics and Automation (ICRA), Seattle, USA, 2015. http://hdl.handle.net/10630/9966 Automatización A Primal-Dual Framework for Real-Time Dense RGB-D Scene Flow