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Liu et al., 2022 - Google Patents

Rethinking of learning-based 3D keypoints detection for large-scale point clouds registration

Liu et al., 2022

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Document ID
6725789036844762687
Author
Liu S
Wang T
Zhang Y
Zhou R
Dai C
Zhang Y
Lei H
Wang H
Publication year
Publication venue
International Journal of Applied Earth Observation and Geoinformation

External Links

Snippet

The main solution for large-scale point clouds registration is to first obtain a set of matched 3D keypoint pairs and then accomplish the point cloud registration task based on these matched keypoint pairs. However, at present, many methods study the feature descriptors in …
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Classifications

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    • G06K9/62—Methods or arrangements for recognition using electronic means
    • 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
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    • G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
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    • G06K9/46—Extraction of features or characteristics of the image
    • G06K9/4671—Extracting features based on salient regional features, e.g. Scale Invariant Feature Transform [SIFT] keypoints
    • G—PHYSICS
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    • G06K9/62—Methods or arrangements for recognition using electronic means
    • G06K9/6267—Classification techniques
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