A Method for 6D Pose Estimation of Free-Form Rigid Objects Using Point Pair Features on Range Data.
Sensors (Basel)
; 18(8)2018 Aug 15.
Article
em En
| MEDLINE
| ID: mdl-30111697
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.
Texto completo:
1
Base de dados:
MEDLINE
Tipo de estudo:
Prognostic_studies
Idioma:
En
Revista:
Sensors (Basel)
Ano de publicação:
2018
Tipo de documento:
Article
País de afiliação:
Taiwan