6DOF Pose Estimation of a 3D Rigid Object based on Edge-enhanced Point Pair Features

• URL: http://arxiv.org/abs/2209.08266v1
• Date: Sat, 17 Sep 2022 07:05:50 GMT
• Title: 6DOF Pose Estimation of a 3D Rigid Object based on Edge-enhanced Point Pair Features
• Authors: Chenyi Liu, Fei Chen, Lu Deng, Renjiao Yi, Lintao Zheng, Chenyang Zhu, Jia Wang, Kai Xu
• Abstract summary: We propose an efficient 6D pose estimation method based on the point pair feature (PPF) framework. A pose hypothesis validation approach is proposed to resolve the symmetric ambiguity by calculating edge matching degree.
• Score: 20.33119373900788
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: The point pair feature (PPF) is widely used for 6D pose estimation. In this paper, we propose an efficient 6D pose estimation method based on the PPF framework. We introduce a well-targeted down-sampling strategy that focuses more on edge area for efficient feature extraction of complex geometry. A pose hypothesis validation approach is proposed to resolve the symmetric ambiguity by calculating edge matching degree. We perform evaluations on two challenging datasets and one real-world collected dataset, demonstrating the superiority of our method on pose estimation of geometrically complex, occluded, symmetrical objects. We further validate our method by applying it to simulated punctures.

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