Real-Time LiDAR Point Cloud Compression Using Bi-Directional Prediction and Range-Adaptive Floating-Point Coding
Author:
Affiliation:
1. School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China
2. School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore
Funder
Nanyang Technological University & Wallenberg AI, Autonomous Systems and Software Program Joint Project
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Media Technology
Link
http://xplorestaging.ieee.org/ielx7/11/9875129/09745995.pdf?arnumber=9745995
Reference58 articles.
1. A 3-D Scan Matching using Improved 3-D Normal Distributions Transform for Mobile Robotic Mapping
2. Adaptive Deep Learning-Based Point Cloud Geometry Coding
3. Adaptive Geometry Partition for Point Cloud Compression
4. Graph-Based Static 3D Point Clouds Geometry Coding
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