Difference between revisions of "Point Cloud"

Revision as of 11:24, 3 November 2019

Deep learning with point clouds | Romain Thalineau - qwertee.io
RS-CNN: Relation-Shape Convolutional Neural Network for Point Cloud Analysis | Y. Liu, B. Fin, S. Xiang, and C. Pan - University of Chinese Academy of Sciences
Point Cloud Library (PCL) is a standalone, large scale, open project for 2D/3D image and point cloud processing.
Screening; Passenger, Luggage, & Cargo
3D Model e.g. 3DCNN
Graph Convolutional Network (GCN), Graph Neural Networks (Graph Nets), Geometric Deep Learning
Common 3D point cloud file formats & solving interoperability issues | Charles Thomson - Vercator

A point cloud is a set of data points in space. Point clouds are generally produced by 3D scanners, which measure a large number of points on the external surfaces of objects around them. As the output of 3D scanning processes, point clouds are used for many purposes, including to create 3D CAD models for manufactured parts, for metrology and quality inspection, and for a multitude of visualization, animation, rendering and mass customization applications. [A point cloud is a set of data points in space. Point clouds are generally produced by 3D scanners, which measure a large number of points on the external surfaces of objects around them. As the output of 3D scanning processes, point clouds are used for many purposes, including to create 3D CAD models for manufactured parts, for metrology and quality inspection, and for a multitude of visualization, animation, rendering and mass customization applications. Point Cloud and List of programs for Point Cloud processing | Wikipedia

Although Convolutional Neural Networks are the state of the art techniques for 2D object detection, they do not perform well on 3D point cloud due to the sparse sensor data, therefore new techniques are needed. 3D Object Detection from LiDAR Data with Deep Learning | SmartLab AI - Medium