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Fast 3D Keypoints Detector and Descriptor for View-Based 3D Objects Recognition
[chapter]
2013
Lecture Notes in Computer Science
In this paper, we propose a new 3D object recognition method that employs a set of 3D keypoints extracted from point cloud representation of 3D views. The method makes use of the 2D organization of range data produced by 3D sensor. Our novel 3D interest points approach relies on surface type classification and combines the Shape Index (SI) -curvedness(C) map with the Gaussian (H) -Mean (K) map. For each extracted keypoint, a local description using the point and its neighbors is computed by
doi:10.1007/978-3-642-40303-3_12
fatcat:o6yezfqoknhybj6qqtuv2yu42i