We discuss theory and application of extended object tracking. This task is challenging as sensor noise prevents a correct association of the measurements to their sources on the object, the shape itself might be unknown a priori, and due to occlusion effects, only parts of the object are visible at a given time. We propose an approach to track the parameters of arbitrary objects, which provides new solutions to the above challenges, and marks a significant advance to the state of the art.
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Faion, F. 2016. Tracking Extended Objects in Noisy Point Clouds with Application in Telepresence Systems. Karlsruhe: KIT Scientific Publishing. DOI: https://doi.org/10.5445/KSP/1000054248
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Veröffentlicht am 13. September 2016