| Submission name | |||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| Submission time (UTC) | July 31, 2019, 5:06 a.m. | ||||||||||
| User | Berti | ||||||||||
| Task | Model-based 6D localization of seen objects | ||||||||||
| Dataset | LM | ||||||||||
| Training model type | Default | ||||||||||
| Training image type | None | ||||||||||
| Description | |||||||||||
| Evaluation scores |
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| User | Berti |
|---|---|
| Publication | Drost et al., Model globally, match locally: Efficient and robust 3D object recognition, CVPR 2010 |
| Implementation | |
| Training image modalities | None |
| Test image modalities | D |
| Description | An implementation of the paper, including ICP for post-processing. The parameters are set to a slower, but more accurate mode (relative sampling distance of 0.03 for model creation and matching). No images are used. CPU only, no GPU is used. The training is done using the CAD models only. Implementation: HALCON 19.05 progress. |
| Computer specifications | Max. 12 Threads on intel Xeon CPU E5-2690 v4 @ 2.60GHz, 2601 Mhz |