Details

Autor(en) / Beteiligte

• Baowei Lin
• Fangda Zhao
• Tamaki, Toru
• Fasheng Wang
• Le Xiao

Titel

SIPF: Scale invariant point feature for 3D point clouds

Ist Teil von

• 2015 IEEE International Conference on Image Processing (ICIP), 2015, p.2611-2615

Ort / Verlag

IEEE

Erscheinungsjahr

2015

Quelle

IEEE Xplore

Beschreibungen/Notizen

• In this paper, we propose a method for detecting Scale-Invariant Point Feature(SIPF) including 3D keypoints Detector and feature descriptor. To detect SIPF, we first estimate a keyscale for point cloud, and calculate the covariance matrix of each 3D point. Keypoints are the saliency points who have a fast change speed along with all principal directions. Then the descriptors are encoded based on the shape of a border or silhouette of an object to be detected or recognized. Experimental results with the Stanford datasets demonstrate that the proposed method can be effectively used for 3D point clouds expression.