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Sensors 2018, 18(11), 3876; https://doi.org/10.3390/s18113876

Deep CNNs with Robust LBP Guiding Pooling for Face Recognition

1
Science and Technology on Microsystem Laboratory, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai 201800, China
2
University of Chinese Academy of Sciences, Beijing 100049, China
3
International Business Machines Corporation, Shanghai 201800, China
*
Author to whom correspondence should be addressed.
Received: 10 October 2018 / Revised: 7 November 2018 / Accepted: 8 November 2018 / Published: 10 November 2018
(This article belongs to the Special Issue Deep Learning-Based Image Sensors)
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Abstract

Pooling layer in Convolutional Neural Networks (CNNs) is designed to reduce dimensions and computational complexity. Unfortunately, CNN is easily disturbed by noise in images when extracting features from input images. The traditional pooling layer directly samples the input feature maps without considering whether they are affected by noise, which brings about accumulated noise in the subsequent feature maps as well as undesirable network outputs. To address this issue, a robust Local Binary Pattern (LBP) Guiding Pooling (G-RLBP) mechanism is proposed in this paper to down sample the input feature maps and lower the noise impact simultaneously. The proposed G-RLBP method calculates the weighted average of all pixels in the sliding window of this pooling layer as the final results based on their corresponding probabilities of being affected by noise, thus lowers the noise impact from input images at the first several layers of the CNNs. The experimental results show that the carefully designed G-RLBP layer can successfully lower the noise impact and improve the recognition rates of the CNN models over the traditional pooling layer. The performance gain of the G-RLBP is quite remarkable when the images are severely affected by noise. View Full-Text
Keywords: pooling layer; CNNs; noise; LBP; feature maps pooling layer; CNNs; noise; LBP; feature maps
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Ma, Z.; Ding, Y.; Li, B.; Yuan, X. Deep CNNs with Robust LBP Guiding Pooling for Face Recognition. Sensors 2018, 18, 3876.

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