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We present a new descriptor for tactile 3D object classification. It is invariant to object movement and simple to construct, using only the relative geometry of points on the object surface. We demonstrate successful classification of 185 objects in 10 categories, at sparse to dense surface sampling rate in point cloud simulation, with an accuracy of 77.5% at the sparsest and 90.1% at the densest...
We present a novel approach for classifying items from a pile of laundry. The classification procedure exploits color, texture, shape, and edge information from 2D and 3D local and global information for each article of clothing using a Kinect sensor. The key contribution of this paper is a novel method of classifying clothing which we term L-M-H, more specifically L-C-S-H using characteristics and...
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