University of Surrey

Test tubes in the lab Research in the ATI Dance Research

SPLODE: Semi-probabilistic point and line odometry with depth estimation from RGB-D camera motion

Proenca, Pedro and Gao, Yang (2018) SPLODE: Semi-probabilistic point and line odometry with depth estimation from RGB-D camera motion In: 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 24-28 Sep 2017, Vancouver, British Columbia, Canada..

SPLODE.pdf - Accepted version Manuscript

Download (2MB) | Preview


Active depth cameras suffer from several limitations, which cause incomplete and noisy depth maps, and may consequently affect the performance of RGB-D Odometry. To address this issue, this paper presents a visual odometry method based on point and line features that leverages both measurements from a depth sensor and depth estimates from camera motion. Depth estimates are generated continuously by a probabilistic depth estimation framework for both types of features to compensate for the lack of depth measurements and inaccurate feature depth associations. The framework models explicitly the uncertainty of triangulating depth from both point and line observations to validate and obtain precise estimates. Furthermore, depth measurements are exploited by propagating them through a depth map registration module and using a frame-to-frame motion estimation method that considers 3D-to-2D and 2D-to-3D reprojection errors, independently. Results on RGB-D sequences captured on large indoor and outdoor scenes, where depth sensor limitations are critical, show that the combination of depth measurements and estimates through our approach is able to overcome the absence and inaccuracy of depth measurements.

Item Type: Conference or Workshop Item (Conference Paper)
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering
Authors :
Date : February 2018
DOI : 10.1109/IROS.2017.8205967
Copyright Disclaimer : Copyright © 2017, IEEE
Uncontrolled Keywords : Cameras; Three-dimensional displays; Uncertainty; Pose estimation; Measurement uncertainty; Simultaneous localization and mapping
Additional Information : Printed proceedings published by Curran Associates, Inc. Available from
Depositing User : Clive Harris
Date Deposited : 14 Mar 2018 11:02
Last Modified : 16 Jan 2019 19:08

Actions (login required)

View Item View Item


Downloads per month over past year

Information about this web site

© The University of Surrey, Guildford, Surrey, GU2 7XH, United Kingdom.
+44 (0)1483 300800