3D face recognition using depth filtering and deep convolutional neural network

Konstantin Dorofeev; Alexey Ruchay; Anastasia Kober; Vitaly Kober

doi:10.1117/12.2527541

6 September 2019 3D face recognition using depth filtering and deep convolutional neural network

Konstantin Dorofeev, Alexey Ruchay, Anastasia Kober, Vitaly Kober

Proceedings Volume 11137, Applications of Digital Image Processing XLII; 111371Y (2019) https://doi.org/10.1117/12.2527541
Event: SPIE Optical Engineering + Applications, 2019, San Diego, California, United States

Abstract

In this paper, we first estimate the accuracy of 3D facial surface reconstruction from real RGB-D depth maps using various depth filtering algorithms. Next, a new 3D face recognition algorithm using deep convolutional neural network is proposed. With the help of 3D face augmentation techniques different facial expressions from a single 3D face scan are synthesized and used for network learning. The performance of the proposed algorithm is compared in terms of 3D face recognition metrics and processing time with that of common 3D face recognition algorithms.

Citation Download Citation

Konstantin Dorofeev, Alexey Ruchay, Anastasia Kober, and Vitaly Kober "3D face recognition using depth filtering and deep convolutional neural network", Proc. SPIE 11137, Applications of Digital Image Processing XLII, 111371Y (6 September 2019); https://doi.org/10.1117/12.2527541

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