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Simulation-based evaluation of predictive tracking for sorting bulk materials

: Pfaff, F.; Pieper, C.; Maier, Georg; Noack, B.; Kruggel-Emden, H.; Gruna, Robin; Hanebeck, U.; Wirtz, S.; Scherer, V.; Längle, Thomas; Beyerer, Jürgen

Postprint urn:nbn:de:0011-n-4357595 (305 KByte PDF)
MD5 Fingerprint: c18c30957ea263daa424b06ffb2160e5
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Created on: 28.2.2017

Institute of Electrical and Electronics Engineers -IEEE-:
IEEE International Conference on Multisensor Fusion and lntegration for Intelligent Systems, MFI 2016 : Sept 19-21, 2016, Baden-Baden, Germany
Piscataway, NJ: IEEE, 2016
ISBN: 978-1-4673-9708-7
ISBN: 978-1-4673-9709-4
International Conference on Multisensor Fusion and lntegration for Intelligent Systems (MFI) <2016, Baden-Baden>
Conference Paper, Electronic Publication
Fraunhofer IOSB ()

Multitarget tracking problems arise in many realworld applications. The performance of the utilized algorithm strongly depends both on how the data association problem is handled and on the suitability of the motion models employed. Especially the motion models can be hard to validate. Previously, we have proposed to use multitarget tracking to improve optical belt sorters. In this paper, we evaluate both the suitability of our model and the tracking and then of our entire system incorporating the image processing component via the use of highly realistic numerical simulations. We first assess the model using noise-free measurements generated by the simulation and then evaluate the entire system by using synthetically generated image data.