Alexander Narr

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We present a next-best-scan (NBS) planning approach for autonomous 3D modeling. The system successively completes a 3D model from complex shaped objects by iteratively selecting a NBS based on previously acquired data. For this purpose, new range data is accumulated in-the-loop into a 3D surface (streaming reconstruction) and new continuous scan paths along(More)
Following an approach proposed by Hutchinson/Lo/Poggio[1994], Kelly[1994] and Malliaris/Salchenberger[1993], we used neural networks to value derivatives. We rst examined the ability of the used neural networks to interpolate the Black & Scholes formula and its derivatives. In a second step we trained neural networks on real world data from the Deutsche(More)
We present a new Active Learning approach for classifying objects from streams of 3D point cloud data. The major problems here are the non-uniform occurrence of class instances and the unbalanced numbers of samples per class. We show that standard online learning methods based on decision trees perform comparably bad for such data streams, which are however(More)
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