BIP! Finder - SnapNet: 3D point cloud semantic labeling with 2D deep segmentation networks

2018 • SnapNet: 3D point cloud semantic labeling with 2D deep segmentation networks

Authors: Alexandre Boulch; Joris Guerry; Bertrand Le Saux; Nicolas Audebert

Venue: Computers & Graphics

Type: Publication

Abstract: Abstract In this work, we describe a new, general, and efficient method for unstructured point cloud labeling. As the question of efficiently using deep Convolutional Neural Networks (CNNs) on 3D data is still a pending issue, we propose a framework which applies CNNs on multiple 2D image views (or snapshots) of the point cloud. The approach consists in three core ideas. (i) We pick many suitable snapshots of the point cloud. We generate two types of images: a Red-Green-Blue (RGB) view and a depth composite view containing geometric features. (... (read more)

Impact:

2.4597153E-7 3.109635E-8 293 106

/ Attention: 0 4

Topics: Artificial intelligence Computer vision

DOI: 10.1016/j.cag.2017.11.010

External links: Crossref OpenAIRE

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