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.Comment: 16 pages,20 figure