Back to articles
Volume: 32 | Article ID: art00023
Indoor Layout Estimation by 2D LiDAR and Camera Fusion
  DOI :  10.2352/ISSN.2470-1173.2020.14.COIMG-391  Published OnlineJanuary 2020

This paper presents an algorithm for indoor layout estimation and reconstruction through the fusion of a sequence of captured images and LiDAR data sets. In the proposed system, a movable platform collects both intensity images and 2D LiDAR information. Pose estimation and semantic segmentation is computed jointly by aligning the LiDAR points to line segments from the images. For indoor scenes with walls orthogonal to floor, the alignment problem is decoupled into top-down view projection and a 2D similarity transformation estimation and solved by the recursive random sample consensus (R-RANSAC) algorithm. Hypotheses can be generated, evaluated and optimized by integrating new scans as the platform moves throughout the environment. The proposed method avoids the need of extensive prior training or a cuboid layout assumption, which is more effective and practical compared to most previous indoor layout estimation methods. Multi-sensor fusion allows the capability of providing accurate depth estimation and high resolution visual information.

Subject Areas :
Views 29
Downloads 5
 articleview.views 29
 articleview.downloads 5
  Cite this article 

Jieyu Li, Robert L. Stevenson, "Indoor Layout Estimation by 2D LiDAR and Camera Fusionin Proc. IS&T Int’l. Symp. on Electronic Imaging: Computational Imaging XVIII,  2020,  pp 391-1 - 391-7,

 Copy citation
  Copyright statement 
Copyright © Society for Imaging Science and Technology 2020
Electronic Imaging
Society for Imaging Science and Technology
7003 Kilworth Lane, Springfield, VA 22151 USA