B-SHOT: A binary feature descriptor for fast and efficient keypoint matching on 3D point clouds. Prakhya, S., M., Liu, B., & Lin, W. In 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages 1929-1934, 9, 2015.
doi  abstract   bibtex   
In this paper, we introduce the very first `binary' 3D feature descriptor, B-SHOT, for fast and efficient keypoint matching on 3D point clouds. We propose a binary quantization method that converts a real valued vector to a binary vector. We apply this method on a state-of-the-art 3D feature descriptor, SHOT [1], and create a new binary 3D feature descriptor. B-SHOT requires 32 times lesser memory for its representation while being 6 times faster in feature descriptor matching, when compared to the SHOT feature descriptor. Experimental evaluation shows that B-SHOT offers comparable keypoint matching performance to that of the state-of-the-art 3D feature descriptors on a standard benchmark dataset.
@inproceedings{
 title = {B-SHOT: A binary feature descriptor for fast and efficient keypoint matching on 3D point clouds},
 type = {inproceedings},
 year = {2015},
 keywords = {Bismuth,Detectors,Electronic mail,Histograms,Memory management,Silicon,Three-dimensional displays},
 pages = {1929-1934},
 month = {9},
 id = {440bb114-773e-31cc-819b-bfb8859cfb56},
 created = {2022-03-28T09:45:05.362Z},
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 profile_id = {235249c2-3ed4-314a-b309-b1ea0330f5d9},
 group_id = {1ff583c0-be37-34fa-9c04-73c69437d354},
 last_modified = {2022-03-30T07:22:29.198Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 citation_key = {prakhyaBSHOTBinaryFeature2015a},
 source_type = {inproceedings},
 short_title = {B-SHOT},
 private_publication = {false},
 abstract = {In this paper, we introduce the very first `binary' 3D feature descriptor, B-SHOT, for fast and efficient keypoint matching on 3D point clouds. We propose a binary quantization method that converts a real valued vector to a binary vector. We apply this method on a state-of-the-art 3D feature descriptor, SHOT [1], and create a new binary 3D feature descriptor. B-SHOT requires 32 times lesser memory for its representation while being 6 times faster in feature descriptor matching, when compared to the SHOT feature descriptor. Experimental evaluation shows that B-SHOT offers comparable keypoint matching performance to that of the state-of-the-art 3D feature descriptors on a standard benchmark dataset.},
 bibtype = {inproceedings},
 author = {Prakhya, Sai Manoj and Liu, Bingbing and Lin, Weisi},
 doi = {10.1109/IROS.2015.7353630},
 booktitle = {2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)}
}

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