Abstract
This paper presents the design of a low cost large-scale 3D scanner. A pan-tilt unit, a camera and a laser distance meter are combined to capture the required range and intensity data. Innovative methods for calibrating the device and fusion of the intensity and range data are introduced. Once a reliable data achieved, a parametric segmentation technique has been adopted to segment the range images into planar surfaces. Experimental results show that even for data corrupted by a large number of outliers (due to people movement in front of the imaged buildings), range and intensity data are highly consistence and segmentation algorithm has been able to properly segment coplanar areas.
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