3-D Point Cloud Registration Using Convolutional Neural Networks

3-D Point Cloud Registration Using Convolutional Neural Networks

This paper develops a registration architecture for the purpose of estimating relative pose including the rotation and the translation of an object in terms of a model in 3-D space based on 3-D point clouds captured by a 3-D camera. Particularly, this paper addresses the time-consuming problem of 3-...

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Bibliographic Details
Main Authors: Wen-Chung Chang, Van-Toan Pham
Format: Article
Language:English
Published: MDPI AG 2019-08-01
Series:Applied Sciences
Subjects:
convolutional neural networks (CNNs)
Iterative Closest Point (ICP)
point cloud
RANdom SAmple Consensus (RANSAC)
3-D registration
Online Access:https://www.mdpi.com/2076-3417/9/16/3273

Internet

https://www.mdpi.com/2076-3417/9/16/3273

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