Keypoints-based surface representation for 3D modeling and 3D object recognition

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• 作者：Syed Afaq Ali Shah^a ; ^{syed.shah@research.uwa.edu.au}Author Vitae ; Mohammed Bennamoun^aAuthor Vitae ; Farid Boussaid^bAuthor Vitae
• 关键词：3D modeling ; 3D Object recognition ; Range images ; Keypoints
• 刊名：Pattern Recognition
• 出版年：2017
• 出版时间：April 2017
• 年：2017
• 卷：64
• 期：Complete
• 页码：29-38
• 全文大小：1265 K
• 卷排序：64

文摘

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.