Name
Title | ||
|---|---|---|
A Method for 6D Pose Estimation of Free-Form Rigid Objects Using Point Pair Features on Range Data. |
Abstract | ||
|---|---|---|
Pose estimation of free-form objects is a crucial task towards flexible and reliable highly complex autonomous systems. Recently, methods based on range and RGB-D data have shown promising results with relatively high recognition rates and fast running times. On this line, this paper presents a feature-based method for 6D pose estimation of rigid objects based on the Point Pair Features voting approach. The presented solution combines a novel preprocessing step, which takes into consideration the discriminative value of surface information, with an improved matching method for Point Pair Features. In addition, an improved clustering step and a novel view-dependent re-scoring process are proposed alongside two scene consistency verification steps. The proposed method performance is evaluated against 15 state-of-the-art solutions on a set of extensive and variate publicly available datasets with real-world scenarios under clutter and occlusion. The presented results show that the proposed method outperforms all tested state-of-the-art methods for all datasets with an overall 6.6% relative improvement compared to the second best method. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.3390/s18082678 | SENSORS |
Keywords | Field | DocType |
computer vision,range data,6D pose estimation,3D object recognition,scene understanding,model-based vision | Random variate,Pattern recognition,Clutter,Electronic engineering,Pose,Preprocessor,Artificial intelligence,Autonomous system (Internet),RGB color model,Engineering,Cluster analysis,Discriminative model | Journal |
Volume | Issue | Citations |
18 | 8.0 | 9 |
PageRank | References | Authors |
0.75 | 5 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Joel Vidal | 1 | 9 | 1.42 |
| Chyi-Yeu Lin | 2 | 71 | 14.95 |
| Xavier Llado | 3 | 578 | 40.04 |
| Robert Martí | 4 | 206 | 17.19 |