|Submission time (UTC)||Aug. 12, 2019, 12:23 p.m.|
|Task||Pose estimation (BOP 2019-2022)|
|Training model type||Default|
|Training image type||None|
|Publication||Drost et al., Model globally, match locally: Efficient and robust 3D object recognition, CVPR 2010.|
|Training image modalities||None|
|Test image modalities||RGB-D|
An implementation of the paper, including - ICP for post-processing - using 3D surface and 3D edges for voting - using 3D surface, 3D edges and 2D images for refinement
The parameters are set to a slower, but more accurate mode (relative sampling distance of 0.03 for model creation and matching). CPU only, no GPU is used.
Implementation: HALCON 19.05 progress.
|Computer specifications||Max. 12 Threads on intel Xeon CPU E5-2690 v4 @ 2.60GHz, 2601 Mhz|