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International Conference on Advanced Concepts for Intelligent Vision Systems

ACIVS 2020: Advanced Concepts for Intelligent Vision Systems pp 15–26Cite as

EpNet: A Deep Neural Network for Ear Detection in 3D Point Clouds

Part of the Lecture Notes in Computer Science book series (LNIP,volume 12002)

Abstract

The human ear is full of distinctive features, and its rigidness to facial expressions and ageing has made it attractive to biometric research communities. Accurate and robust ear detection is one of the essential steps towards biometric systems, substantially affecting the efficiency of the entire identification system. Existing ear detection methods are prone to failure in the presence of typical day-to-day circumstances, such as partial occlusions due to hair or accessories, pose variations, and different lighting conditions. Recently, some researchers have proposed different state-of-the-art deep neural network architectures for ear detection in two-dimensional (2D) images. However, the ear detection directly from three-dimensional (3D) point clouds using deep neural networks is still an unexplored problem. In this work, we propose a deep neural network architecture named EpNet for 3D ear detection, which can detect ear directly from 3D point clouds. We also propose an automatic pipeline to annotate ears in the profile face images of UND J2 public data set. The experimental results on the public data show that our proposed method can be an effective solution for 3D ear detection.

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Author information

Authors and Affiliations

  1. Edith Cowan University, Joondalup, WA, 6027, Australia

    Md Mursalin & Syed Mohammed Shamsul Islam

  2. University of Western Australia, Crawley, WA, 6009, Australia

    Syed Mohammed Shamsul Islam

Authors
  1. Md Mursalin
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  2. Syed Mohammed Shamsul Islam
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Corresponding author

Correspondence to Md Mursalin .

Editor information

Editors and Affiliations

  1. DGA, Paris, France

    Jacques Blanc-Talon

  2. University of Auckland, Auckland, New Zealand

    Patrice Delmas

  3. Ghent University, Ghent, Belgium

    Wilfried Philips

  4. CSIRO, Canberra, Australia

    Dan Popescu

  5. University of Antwerp, Wilrijk, Belgium

    Paul Scheunders

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Mursalin, M., Islam, S.M.S. (2020). EpNet: A Deep Neural Network for Ear Detection in 3D Point Clouds. In: Blanc-Talon, J., Delmas, P., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2020. Lecture Notes in Computer Science(), vol 12002. Springer, Cham. https://doi.org/10.1007/978-3-030-40605-9_2

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  • DOI: https://doi.org/10.1007/978-3-030-40605-9_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-40604-2

  • Online ISBN: 978-3-030-40605-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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