Whelan, Thomas and Kaess, Michael and Fallon, Maurice and Johannsson, Hordur and Leonard, John J. and McDonald, John (2012) Kintinuous: Spatially Extended KinectFusion. In: RSS Workshop on RGB-D: Advanced Reasoning with Depth Cameras, July 9-13, 2012, Sydney.

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Abstract

In this paper we present an extension to the KinectFusion algorithm that permits dense mesh-based mapping of extended scale environments in real-time. This is achieved through (i) altering the original algorithm such that the region of space being mapped by the KinectFusion algorithm can vary dynamically, (ii) extracting a dense point cloud from the regions that leave the KinectFusion volume due to this variation, and, (iii) incrementally adding the resulting points to a triangular mesh representation of the environment. The system is implemented as a set of hierarchical multi-threaded components which are capable of operating in real-time. The architecture facilitates the creation and integration of new modules with minimal impact on the performance on the dense volume tracking and surface reconstruction modules. We provide experimental results demonstrating the system’s ability to map areas considerably beyond the scale of the original KinectFusion algorithm including a two story apartment and an extended sequence taken from a car at night. In order to overcome failure of the iterative closest point (ICP) based odometry in areas of low geometric features we have evaluated the Fast Odometry from Vision (FOVIS) system as an alternative. We provide a comparison between the two approaches where we show a trade off between the reduced drift of the visual odometry approach and the higher local mesh quality of the ICP-based approach. Finally we present ongoing work on incorporating full simultaneous localisation and mapping (SLAM) pose-graph optimisation.

Item Type:	Conference or Workshop Item (Paper)
Additional Information:	Research presented in this paper was funded by a Strategic Research Cluster grant (07/SRC/I1168) by Science Foundation Ireland under the Irish National Development Plan and the Embark Initiative of the Irish Research Council for Science, Engineering and Technology.
Keywords:	Kintinuous; KinectFusion; Fast Odometry from Vision (FOVIS); full simultaneous localisation and mapping (SLAM);
Academic Unit:	Faculty of Science and Engineering > Computer Science
Item ID:	8316
Depositing User:	John McDonald
Date Deposited:	13 Jun 2017 09:05
Refereed:	Yes
URI:
Use Licence:	This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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