Optimization Method of 3D Point Cloud Generation for Underwater Target-Reference-Cited by-同舟云学术

Optimization Method of 3D Point Cloud Generation for Underwater Target

Published:2022-12-09 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2022 6th International Conference on Computer Science and Artificial Intelligence
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Author:

Qin Hao¹^ORCID,Yang Renyou¹^ORCID,Zheng Kaijian¹^ORCID,Yang Liang¹^ORCID,Li Rifu¹^ORCID

Affiliation:

1. Southern Marine Science and Engineering Guangdong Laboratory (Zhanjiang), China

Funder

Development of large cruising aquaculture platform in the South China Sea

Fund of Zhanjiang Municipal Bureau of Science and Technology

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3577530.3577548

Reference27 articles.

1. Lucas B D . An iterative image registration technique with an application to stereo vision [C] . proceedings of the Proc DARPA Image Understanding Workshop , 1981 . Lucas B D. An iterative image registration technique with an application to stereo vision [C]. proceedings of the Proc DARPA Image Understanding Workshop, 1981.

2. Tomasi C , Kanade T. Detection and Tracking of Point Features [J] . International Journal of Computer Vision , 1991 , 9 ( 3 ): 137 - 154 . Tomasi C, Kanade T. Detection and Tracking of Point Features [J]. International Journal of Computer Vision, 1991, 9(3): 137-54.

3. Derivation of Kanade-Lucas-Tomasi Tracking Equation [J]. School of Computer Science, Carnegie Mellon University;Birchfield S;Pittsburgh,1997

4. Frahm S , Pollefeys M , Genc Y. GPU-based Video Feature Tracking And Matching [J] . Workshop on Edge Computing Using New Commodity Architectures, 2006 , 2000 (Oct 21): 189 - 196 . Frahm S, Pollefeys M, Genc Y. GPU-based Video Feature Tracking And Matching [J]. Workshop on Edge Computing Using New Commodity Architectures, 2006, 2000(Oct 21): 189-96.