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 language | English |
---|---|
Title of host publication | 2016 IEEE International Conference on Robotics and Automation (ICRA 2016) |
Subtitle of host publication | Proceedings of a meeting held 16-21 May 2016, Stockholm, Sweden |
Publisher | Institute of Electrical and Electronics Engineers (IEEE) |
Pages | 1323-1330 |
Number of pages | 8 |
ISBN (Print) | 9781467380270 |
DOIs | |
Publication status | Published - 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
Fingerprint
Dive into the research topics of 'Fast depth edge detection and edge based RGB-D SLAM'. Together they form a unique fingerprint.Student Theses
-
Edge Based RGB-D SLAM and SLAM Based Navigation
Author: Bose, L. N., 7 Mar 2017Supervisor: Richards, A. G. (Supervisor)
Student thesis: Doctoral Thesis › Doctor of Philosophy (PhD)
File