REMODE: Probabilistic, monocular dense reconstruction in real time

Matia Pizzoli, Christian Forster, Davide Scaramuzza
2014 2014 IEEE International Conference on Robotics and Automation (ICRA)  
In this paper, we solve the problem of estimating dense and accurate depth maps from a single moving camera. A probabilistic depth measurement is carried out in real time on a per-pixel basis and the computed uncertainty is used to reject erroneous estimations and provide live feedback on the reconstruction progress. Our contribution is a novel approach to depth map computation that combines Bayesian estimation and recent development on convex optimization for image processing. We demonstrate
more » ... at our method outperforms stateof-the-art techniques in terms of accuracy, while exhibiting high efficiency in memory usage and computing power. We call our approach REMODE (REgularized MOnocular Depth Estimation) and the CUDA-based implementation runs at 30Hz on a laptop computer.
doi:10.1109/icra.2014.6907233 dblp:conf/icra/PizzoliFS14 fatcat:7vjx2dhbcnemtkccw4q5xtc4du