Keypoints-based surface representation for 3D modeling and 3D object recognition
作者：
Highlights：
• We propose a novel technique, called Keypoint-based Surface Representation (KSR).
• The proposed technique does not require local features around detected keypoints.
• KSR exploits geometrical relationships between keypoints for surface representation.
• KSR is tested on 3 popular datasets for 3D modeling and 3D object recognition.
• KSR achieves superior 3D modeling and recognition results.
摘要
Highlights•We propose a novel technique, called Keypoint-based Surface Representation (KSR).•The proposed technique does not require local features around detected keypoints.•KSR exploits geometrical relationships between keypoints for surface representation.•KSR is tested on 3 popular datasets for 3D modeling and 3D object recognition.•KSR achieves superior 3D modeling and recognition results.
论文关键词：3D modeling,3D Object recognition,Range images,Keypoints
论文评审过程：Received 27 June 2015, Revised 20 October 2016, Accepted 22 October 2016, Available online 26 October 2016, Version of Record 5 November 2016.
论文官网地址：https://doi.org/10.1016/j.patcog.2016.10.028
