Researchs on the pose estimation pipeline based on feature matching, which is compose of a keypoint descriptor, a feature matcher, a geometric solver and a pose refiner. GMatch is the name of our proposed matcher.

• Possible descriptor: SIFT [1], ORB [2], SuperPoint [3].
• Possible matcher: GMatch, NN (Nearest Neighbour with Lowe's Ratio Test [1]), LightGlue [4].
• Solver: RANSAC from open3d.
• Refiner: ICP from open3d.

[1] David G Lowe. Distinctive image features from scale-invariant keypoints. International journal of computer vision, 60:91–110, 2004.

[2] Ethan Rublee, Vincent Rabaud, Kurt Konolige, and Gary Bradski. Orb: An efficient alternative to sift or surf. In 2011 International conference on computer vision, pages 2564–2571. Ieee, 2011.

[3] Daniel DeTone, Tomasz Malisiewicz, and Andrew Rabinovich. Superpoint: Self-supervised interest point detection and description. In Proceedings of the IEEE conference on computer vision and pattern recognition workshops, pages 224–236, 2018.

[4] Philipp Lindenberger, Paul-Edouard Sarlin, and Marc Pollefeys. Lightglue: Local feature matching at light speed. In Proceedings of the IEEE/CVF International Conference on Computer Vision, pages 17627–17638, 2023.