RT Conference Proceedings
T1 A Primal-Dual Framework for Real-Time Dense RGB-D Scene Flow
A1 Jaimez, Mariano
A1 Souiai, Mohamed
A1 González-Jiménez, Antonio Javier
A1 Cremers, Daniel
K1 Automatización
AB This paper presents the first method to computedense 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) wherequantitative 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.
PB IEEE
YR 2015
FD 2015-05
LK http://hdl.handle.net/10630/9966
UL http://hdl.handle.net/10630/9966
LA eng
NO 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.
NO 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.
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 20 ene 2026