Fast depth edge detection and edge based RGB-D SLAM

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Abstract

This paper presents a method of occluding depth edge-detection targeted towards RGB-D video streams and explores the use of these and other edge features in RGB-D SLAM. The proposed depth edge-detection approach uses prior information obtained from the previous RGB-D video frame to determine which areas of the current depth image are likely to contain edges due to image similarity. By limiting the search for edges to these areas a significant amount of computation time is saved compared to searching the entire image. Pixels belonging to both the depth and colour edges of an RGB-D image can be back projected using the depth component to form 3D point clouds of edge points. Registration between such edge point clouds is achieved using ICP and we present a realtime RGB-D SLAM system utilizing such back projected edge features. Experimental results are presented demonstrating the performance of both the proposed depth edge-detection and SLAM system using publicly available datasets.
Original languageEnglish
Title of host publication2016 IEEE International Conference on Robotics and Automation (ICRA 2016)
Subtitle of host publicationProceedings of a meeting held 16-21 May 2016, Stockholm, Sweden
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages1323-1330
Number of pages8
ISBN (Print)9781467380270
DOIs
Publication statusPublished - Aug 2016

Keywords

  • SLAM (robots)
  • edge detection
  • image colour analysis
  • iterative methods
  • mobile robots
  • robot vision
  • video streaming
  • 3D point clouds
  • ICP
  • RGB-D video streams
  • back projected edge features
  • computation time
  • depth component
  • edge based RGB-D SLAM
  • edge features
  • fast depth edge detection
  • image similarity
  • publicly available datasets
  • Cameras
  • Image edge detection
  • Iterative closest point algorithm
  • Simultaneous localization and mapping
  • Streaming media
  • Three-dimensional displays

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