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A cGANs-based scene reconstruction model using lidar point cloud

  • Beihang University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Road scene reconstruction is a fundamental and crucial module at the perception phase for autonomous vehicles, and will influence the later phase, such as object detection, motion planing and path planing. Traditionally, self-driving car uses Lidar, camera or fusion of the two kinds of sensors for sensing the environment. However, single Lidar or camera-based approaches will miss crucial information, and the fusion-based approaches often consume huge computing resources. We firstly propose a conditional Generative Adversarial Networks (cGANs)-based deep learning model that can rebuild rich semantic scene images from upsampled Lidar point clouds only. This makes it possible to remove cameras to reduce resource consumption and improve the processing rate. Simulation on the KITTI dataset also demonstrates that our model can reestablish color imagery from a single Lidar point cloud, and is effective enough for real time sensing on autonomous driving vehicles.

Original languageEnglish
Title of host publicationProceedings - 15th IEEE International Symposium on Parallel and Distributed Processing with Applications and 16th IEEE International Conference on Ubiquitous Computing and Communications, ISPA/IUCC 2017
EditorsGregorio Martinez, Richard Hill, Geoffrey Fox, Peter Mueller, Guojun Wang
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1107-1114
Number of pages8
ISBN (Electronic)9781538637906
DOIs
StatePublished - 25 May 2018
Event15th IEEE International Symposium on Parallel and Distributed Processing with Applications and 16th IEEE International Conference on Ubiquitous Computing and Communications, ISPA/IUCC 2017 - Guangzhou, China
Duration: 12 Dec 201715 Dec 2017

Publication series

NameProceedings - 15th IEEE International Symposium on Parallel and Distributed Processing with Applications and 16th IEEE International Conference on Ubiquitous Computing and Communications, ISPA/IUCC 2017

Conference

Conference15th IEEE International Symposium on Parallel and Distributed Processing with Applications and 16th IEEE International Conference on Ubiquitous Computing and Communications, ISPA/IUCC 2017
Country/TerritoryChina
CityGuangzhou
Period12/12/1715/12/17

Keywords

  • Autonomous vehicle
  • CGANs
  • Lidar point cloud
  • Scene reconstruction
  • Upsampling

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