Submission: Vidal-Sensors18/YCB-V

Submission name
Submission time (UTC) Oct. 22, 2019, 7:57 a.m.
User jolvid
Dataset YCB-V
Training model type Default
Training image type None
Description
Evaluation scores
bop19_average_recall:0.450
bop19_average_recall_mspd:0.347
bop19_average_recall_mssd:0.380
bop19_average_recall_vsd:0.623
bop19_average_time_per_image:3.719

Method: Vidal-Sensors18

User jolvid
Publication A Method for 6D Pose Estimation of Free-Form Rigid Objects Using Point Pair Features on Range Data, Sensors, 2018, 18.8: 2678.
Implementation
Training image modalities None
Test image modalities D
Description Implementation of the method described in “A Method for 6D Pose Estimation of Free-Form Rigid Objects Using Point Pair Features on Range Data”. The method combines a normal-based clustering preprocessing step with an improved matching method for Point Pair Features. In addition, it includes an agglomerative hypothesis clustering, an efficient view-dependent re-scoring process and two scene consistency verification steps. A simple non-maximum suppression step has been included in postprocessing to account for multiple instances. The parameters used are the ones described in the paper and are not optimized for speed or performance on these datasets. Due to the straight forward adaptation to VIVO task, provided scores are not consistent/meaningful.
Computer specifications Intel(R) Core(TM) i7-8750H CPU @ 2.20GHz