A Method for 6D Pose Estimation of Free-Form Rigid Objects Using Point Pair Features on Range Data

Sensors

Robert Martí¹  Xavier Lladó¹  Joel Vidal²  Chyi-Yeu Lin² 

[1] Computer Vision and Robotics Institute, University of Girona, 17003 Girona, Spain;Department of Mechanical Engineering, National Taiwan University of Science and Technology, Taipei 106, Taiwan;

关键词: computer vision;    range data;    6D pose estimation;    3D object recognition;    scene understanding;    model-based vision;   

DOI  :  10.3390/s18082678

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown