Results for DVO-SLAM
Submission data
Full name | Dense Visual SLAM for RGB-D Cameras |
Description | See: https://vision.in.tum.de/data/software/dvo |
Parameters | Default parameters, but modified to run global optimization after dataset playback finished. |
Publication title | Dense Visual SLAM for RGB-D Cameras |
Publication authors | Christian Kerl, Jürgen Sturm, Daniel Cremers |
Publication venue | IROS 2013 |
Publication URL | https://vision.in.tum.de/_media/spezial/bib/kerl13iros.pdf |
Programming language(s) | C++ |
Hardware | Intel Core i7-6700K |
Website | https://vision.in.tum.de/data/software/dvo |
Source code or download URL | https://github.com/tum-vision/dvo_slam |
Submission creation date | 17 Jun, 2019 |
Last edited | 17 Jun, 2019 |
High-res multi-view results
Info | all | high-res multi-view | indoor | outdoor | botani. | boulde. | bridge | door | exhibi. | lectur. | living. | lounge | observ. | old co. | statue | terrac. |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
No results yet. |
Low-res many-view results
Info | all | low-res many-view | indoor | outdoor | delivery area | electro | forest | playground | terrains |
---|---|---|---|---|---|---|---|---|---|
No results yet. |
Low-res two-view results
SLAM results
all | boxes | boxes dark | buddha | cables 4 | cables 5 | desk 1 | desk 2 | desk changing 2 | desk dark 1 | desk dark 2 | desk global light changes | desk ir light | dino | drone | foreground occlusion | helmet | kidnap 2 | lamp | large loop 2 | large loop 3 | large non loop | motion 2 | motion 3 | motion 4 | planar 1 | reflective 2 | scale change | table 1 | table 2 | table 5 | table 6 | table global light changes | table local light changes | table scene | trashbin | |||
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Method | Info | |||||||||||||||||||||||||||||||||||||
71.83 | 0.59 | fail | 3.59 | fail | 8.79 | 2.25 | fail | fail | 6.16 | fail | fail | 2.43 | fail | fail | 5.39 | 0.36 | fail | fail | fail | fail | fail | fail | fail | fail | fail | fail | fail | 1.01 | fail | 6.50 | 2.00 | 1.10 | 1.24 | 5.68 | 1.87 |