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Zhang et al., 2021 - Google Patents

KDD: A kernel density based descriptor for 3D point clouds

Zhang et al., 2021

Document ID
8699158146232996409
Author
Zhang Y
Li C
Guo B
Guo C
Zhang S
Publication year
Publication venue
Pattern Recognition

External Links

Snippet

Abstract 3D feature description is one of the central techniques that rely on point clouds since a lot of point cloud processing techniques apply the point-to-point correspondences that are achieved via feature descriptors as input data. The feature descriptor encodes the …
Continue reading at www.sciencedirect.com (other versions)

Classifications

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    • G06K9/6201—Matching; Proximity measures
    • G06K9/6202—Comparing pixel values or logical combinations thereof, or feature values having positional relevance, e.g. template matching
    • G06K9/6203—Shifting or otherwise transforming the patterns to accommodate for positional errors
    • G06K9/6211—Matching configurations of points or features, e.g. constellation matching
    • G—PHYSICS
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