Robust Real-Time Visual Odometry for Dense RGB-D Mapping

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“Robust Real-Time Visual Odometry for Dense RGB-D Mapping” by T. Whelan, H. Johannsson, M. Kaess, J.J. Leonard, and J.B. McDonald. In IEEE Intl. Conf. on Robotics and Automation, ICRA, (Karlsruhe, Germany), May 2013.

Abstract

This paper describes extensions to the Kintinuous algorithm for spatially extended KinectFusion, incorporating the following additions: (i) the integration of multiple 6DOF camera odometry estimation methods for robust tracking; (ii) a novel GPU-based implementation of an existing dense RGB-D visual odometry algorithm; (iii) advanced fused real-time surface coloring. These extensions are validated with extensive experimental results, both quantitative and qualitative, demonstrating the ability to build dense fully colored models of spatially extended environments for robotics and virtual reality applications while remaining robust against scenes with challenging sets of geometric and visual features.

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BibTeX entry:

@inproceedings{Whelan13icra,
   author = {T. Whelan and H. Johannsson and M. Kaess and J.J. Leonard and
	J.B. McDonald},
   title = {Robust Real-Time Visual Odometry for Dense {RGB-D} Mapping},
   booktitle = {IEEE Intl. Conf. on Robotics and Automation, ICRA},
   address = {Karlsruhe, Germany},
   month = {May},
   year = {2013}
}
Last updated: June 21, 2014