Robust Tracking for Real-Time Dense RGB-D Mapping with Kintinuous - Robotics Institute Carnegie Mellon University

Robust Tracking for Real-Time Dense RGB-D Mapping with Kintinuous

Thomas Whelan, Hordur Johannsson, Michael Kaess, John J. Leonard, and John McDonald
Tech. Report, Computer Science and Artificial Intelligence Laboratory MIT-CSAIL-TR-2012-031, September, 2012

Abstract

This paper describes extensions to the Kintinu- ous [1] algorithm for spatially extended KinectFusion, incor- porating the following additions: (i) the integration of multiple 6DOF camera odometry estimation methods for robust track- ing; (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 ex- tensive 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.

BibTeX

@techreport{Whelan-2012-7588,
author = {Thomas Whelan and Hordur Johannsson and Michael Kaess and John J. Leonard and John McDonald},
title = {Robust Tracking for Real-Time Dense RGB-D Mapping with Kintinuous},
year = {2012},
month = {September},
institute = {Carnegie Mellon University},
address = {Pittsburgh, PA},
}