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| Type | Conference or Workshop Paper |
| Scope | Discipline-based scholarship |
| Published in Proceedings | Yes |
| Title | REMODE: probabilistic, monocular dense reconstruction in real time |
| Organization Unit | |
| Authors |
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| Presentation Type | paper |
| Item Subtype | Original Work |
| Refereed | Yes |
| Status | Published in final form |
| Language |
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| ISSN | 1050-4729 |
| Page Range | 2609 - 2616 |
| Event Title | IEEE International Conference on Robotics and Automation (ICRA) |
| Event Type | conference |
| Event Location | Hong Kong |
| Event Start Date | May 31 - 2014 |
| Event End Date | June 7 - 2014 |
| Series Name | IEEE International Conference on Robotics and Automation. Proceedings |
| Place of Publication | Hong Kong |
| Publisher | Institute of Electrical and Electronics Engineers |
| Abstract Text | 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 that our method outperforms state-of-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). Our CUDA-based implementation runs at 30Hz on a laptop computer and is released as open-source software. |
| Related URLs |
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| Digital Object Identifier | 10.1109/ICRA.2014.6907233 |
| Other Identification Number | merlin-id:10214 |
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