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Automatic Viewpoint Estimation for Inspection Planning Purposes

 
: Dutta, S.; Rauhut, M.; Hagen, H.; Gospodnetic, P.

:

Bimbo, A. del ; IEEE Computer Society:
Pattern Recognition. ICPR International Workshops and Challenges. Proceedings. Pt.IV : Virtual Event, January 10-15, 2021
Cham: Springer Nature, 2021 (Lecture Notes in Computer Science 12664)
ISBN: 978-3-030-68798-4 (Print)
ISBN: 978-3-030-68799-1 (Online)
pp.675-691
International Conference on Pattern Recognition (ICPR) <25, 2021, Online>
English
Conference Paper
Fraunhofer ITWM ()

Abstract
Viewpoint estimation is an important aspect of surface inspection and planning. Typically viewpoint estimation has been done only with the 3D model and not with the actual object. This, therefore, limits the flexibility of using the actual object in inspection planning. In this work, we present a novel pipeline that can efficiently estimate viewpoints from live camera images. The pipeline can be used for different sized industrial objects to efficiently estimate the viewpoint. The achieved results are real-time and the method is easily generalizable to different objects. The presented method is based on a 3D model of the object, which is self-supervised and requires no manual data annotation or real images to be used as an input. The complete solution, together with documentation and examples is available in the public domain for testing. https://gitlab.itwm.fraunhofer.de/dutta/real-time-pose-est/.

: http://publica.fraunhofer.de/documents/N-637753.html