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Sensors 2014, 14(4), 7563-7579; doi:10.3390/s140407563

A Multi-Resolution Approach for an Automated Fusion of Different Low-Cost 3D Sensors

Institute of Geodesy and Geoinformation, University of Bonn, Nussallee 17, 53115 Bonn, Germany
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Received: 24 January 2014 / Revised: 8 April 2014 / Accepted: 15 April 2014 / Published: 24 April 2014
(This article belongs to the Section Physical Sensors)
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Abstract

The 3D acquisition of object structures has become a common technique in many fields of work, e.g., industrial quality management, cultural heritage or crime scene documentation. The requirements on the measuring devices are versatile, because spacious scenes have to be imaged with a high level of detail for selected objects. Thus, the used measuring systems are expensive and require an experienced operator. With the rise of low-cost 3D imaging systems, their integration into the digital documentation process is possible. However, common low-cost sensors have the limitation of a trade-off between range and accuracy, providing either a low resolution of single objects or a limited imaging field. Therefore, the use of multiple sensors is desirable. We show the combined use of two low-cost sensors, the Microsoft Kinect and the David laserscanning system, to achieve low-resolved scans of the whole scene and a high level of detail for selected objects, respectively. Afterwards, the high-resolved David objects are automatically assigned to their corresponding Kinect object by the use of surface feature histograms and SVM-classification. The corresponding objects are fitted using an ICP-implementation to produce a multi-resolution map. The applicability is shown for a fictional crime scene and the reconstruction of a ballistic trajectory. View Full-Text
Keywords: Microsoft Kinect; David laserscanner; automated sensor fusion; markerless registration; surface feature histograms Microsoft Kinect; David laserscanner; automated sensor fusion; markerless registration; surface feature histograms
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This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Dupuis, J.; Paulus, S.; Behmann, J.; Plümer, L.; Kuhlmann, H. A Multi-Resolution Approach for an Automated Fusion of Different Low-Cost 3D Sensors. Sensors 2014, 14, 7563-7579.

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