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Integrating depth and color cues for dense multi-resolution scene mapping using RGB-D cameras

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2 Author(s)
Stuckler, J. ; Autonomous Intell. Syst. Group, Univ. of Bonn, Bonn, Germany ; Behnke, S.

The mapping of environments is a prerequisite for many navigation and manipulation tasks. We propose a novel method for acquiring 3D maps of indoor scenes from a freely moving RGB-D camera. Our approach integrates color and depth cues seamlessly in a multi-resolution map representation. We consider measurement noise characteristics and exploit dense image neighborhood to rapidly extract maps from RGB-D images. An efficient ICP variant allows maps to be registered in real-time at VGA resolution on a CPU. For simultaneous localization and mapping, we extract key views and optimize the trajectory in a probabilistic framework. Finally, we propose an efficient randomized loop-closure technique that is designed for on-line operation. We benchmark our method on a publicly available RGB-D dataset and compare it with a state-of-the-art approach that uses sparse image features.

Published in:

Multisensor Fusion and Integration for Intelligent Systems (MFI), 2012 IEEE Conference on

Date of Conference:

13-15 Sept. 2012

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