Abstract
Quality assurance programs of today’s car manufacturers show increasing demand for automated visual inspection tasks. A typical example is just-in-time checking of assemblies along production lines. Since high throughput must be achieved, object recognition and pose estimation heavily rely on offline preprocessing stages of available CAD data. In this paper, we propose a complete, universal framework for CAD model feature extraction and entropy index based viewpoint selection that is developed in cooperation with a major german car manufacturer.
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Stößel, D., Hanheide, M., Sagerer, G., Krüger, L., Ellenrieder, M. (2004). Feature and Viewpoint Selection for Industrial Car Assembly. In: Rasmussen, C.E., Bülthoff, H.H., Schölkopf, B., Giese, M.A. (eds) Pattern Recognition. DAGM 2004. Lecture Notes in Computer Science, vol 3175. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-28649-3_65
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DOI: https://doi.org/10.1007/978-3-540-28649-3_65
Publisher Name: Springer, Berlin, Heidelberg
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