A Data-Driven Point Cloud Simplification Framework for City-Scale Image-Based Localization-Reference-Cited by-同舟云学术

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A Data-Driven Point Cloud Simplification Framework for City-Scale Image-Based Localization

Published:2017-01 Issue:1 Volume:26 Page:262-275
ISSN:1057-7149
Container-title:IEEE Transactions on Image Processing
language:
Short-container-title:IEEE Trans. on Image Process.

Author:

Cheng Wentao^ORCID,Lin Weisi^ORCID,Zhang Xinfeng,Goesele Michael,Sun Ming-Ting

Funder

National Research Foundation, Prime Minsters Office, Singapore, under its International Research Centers in Singapore Funding Initiative

Singapore MoE Tier 1 Project

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Graphics and Computer-Aided Design,Software

Link

http://xplorestaging.ieee.org/ielx7/83/7743013/07725940.pdf?arnumber=7725940

Cited by 30 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. MS‐SLAM: Memory‐Efficient Visual SLAM With Sliding Window Map Sparsification;Journal of Field Robotics;2024-09-04

2. A new point cloud simplification algorithm based on V-P container constraint and normal vector angle information entropy;Measurement Science and Technology;2024-06-28

3. Fast subsampling strategy for point cloud based on novel octree coding;Measurement Science and Technology;2024-01-25

4. Fast and Lightweight Scene Regressor for Camera Relocalization;2024 IEEE/SICE International Symposium on System Integration (SII);2024-01-08

5. EGST: Enhanced Geometric Structure Transformer for Point Cloud Registration;IEEE Transactions on Visualization and Computer Graphics;2024

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