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Deformable Surface Registration with Extreme Learning Machines

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Proceedings of ELM-2017 (ELM 2017)

Part of the book series: Proceedings in Adaptation, Learning and Optimization ((PALO,volume 10))

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Abstract

One of the most important open problems in the field of computer-aided design and computer graphics is the task of surface registration for non-isometric cases. One of the approaches of addressing surface registration problem is to find the point-wise correspondence between surfaces using state-of-the-art shape descriptors. This paper introduces an improvement to this approach by means of Extreme Learning Machines. The ELM model is trained to distinguish pairs of corresponding points from non-corresponding ones on the dataset with highly non-isometric distortions between models. The proposed method is compared with original shape descriptors. The results show the increase of accuracy in surface registration task, and also reveal the bottleneck of the state-of-the-art shape descriptors.

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Author information

Authors and Affiliations

  1. Department of Mechanical and Industrial Engineering, The University of Iowa, Iowa City, USA

    Andrey Gritsenko, Zhiyu Sun, Stephen Baek, Renjie Hu & Amaury Lendasse

  2. Iowa Informatics Initiative, The University of Iowa, Iowa City, USA

    Andrey Gritsenko, Renjie Hu & Amaury Lendasse

  3. Center for Computer-Aided Design, The University of Iowa, Iowa City, USA

    Zhiyu Sun & Stephen Baek

  4. Bell Labs, Nokia, Espoo, Finland

    Yoan Miche

  5. Arcada University of Applied Sciences, Helsinki, Finland

    Amaury Lendasse

Authors
  1. Andrey Gritsenko
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  2. Zhiyu Sun
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  3. Stephen Baek
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  4. Yoan Miche
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  5. Renjie Hu
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  6. Amaury Lendasse
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Corresponding author

Correspondence to Andrey Gritsenko .

Editor information

Editors and Affiliations

  1. Institute of Information and Control, Hangzhou Dianzi University, Zhejiang, China

    Jiuwen Cao

  2. Department of Computer and Information Science, University of Macau, Macau, China

    Chi Man Vong

  3. Nokia Bell Labs, Espoo, Finland

    Yoan Miche

  4. Department of Information and Logistics, College of Technology at the University of Houston, Houston, TX, USA

    Amaury Lendasse

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Gritsenko, A., Sun, Z., Baek, S., Miche, Y., Hu, R., Lendasse, A. (2019). Deformable Surface Registration with Extreme Learning Machines. In: Cao, J., Vong, C., Miche, Y., Lendasse, A. (eds) Proceedings of ELM-2017. ELM 2017. Proceedings in Adaptation, Learning and Optimization, vol 10. Springer, Cham. https://doi.org/10.1007/978-3-030-01520-6_28

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