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Authors: Julien Langlois 1 ; Harold Mouchère 2 ; Nicolas Normand 2 and Christian Viard-Gaudin 2

Affiliations: 1 University of Nantes and Multitude-Technologies a company of Wedo, France ; 2 University of Nantes, France

ISBN: 978-989-758-276-9

Keyword(s): Neural Networks, 3D Pose Estimation, 2D Images, Deep Learning, Quaternions, Geodesic Loss, Rendered Data, Data Augmentation.

Related Ontology Subjects/Areas/Topics: Applications ; Feature Selection and Extraction ; Pattern Recognition ; Regression ; Software Engineering ; Theory and Methods ; Virtual Environments

Abstract: In this paper we propose a pose regression method employing a convolutional neural network (CNN) fed with single 2D images to estimate the 3D orientation of a specific industrial part. The network training dataset is generated by rendering pose-views from a textured CAD model to compensate for the lack of real images and their associated position label. Using several lighting conditions and material reflectances increases the robustness of the prediction and allows to anticipate challenging industrial situations. We show that using a geodesic loss function, the network is able to estimate a rendered view pose with a 5 accuracy while inferring from real images gives visually convincing results suitable for any pose refinement processes.

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Paper citation in several formats:
Langlois, J.; Mouchère, H.; Normand, N. and Viard-Gaudin, C. (2018). 3D Orientation Estimation of Industrial Parts from 2D Images using Neural Networks.In Proceedings of the 7th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-276-9, pages 409-416. DOI: 10.5220/0006597604090416

@conference{icpram18,
author={Julien Langlois. and Harold Mouchère. and Nicolas Normand. and Christian Viard{-}Gaudin.},
title={3D Orientation Estimation of Industrial Parts from 2D Images using Neural Networks},
booktitle={Proceedings of the 7th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2018},
pages={409-416},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006597604090416},
isbn={978-989-758-276-9},
}

TY - CONF

JO - Proceedings of the 7th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - 3D Orientation Estimation of Industrial Parts from 2D Images using Neural Networks
SN - 978-989-758-276-9
AU - Langlois, J.
AU - Mouchère, H.
AU - Normand, N.
AU - Viard-Gaudin, C.
PY - 2018
SP - 409
EP - 416
DO - 10.5220/0006597604090416

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