NDLI: Patch strategy for deep face recognition

Content Provider	IET Digital Library
Author	Zhang, Yanhong Shang, Kun Wang, Jun Li, Nan Zhang, Monica M. Y.
Abstract	Convolutional neural network (CNN) has proven to be a highly efficient approach to face recognition. In this study, the authors introduce a new layer to embed the patch strategy in convolutional architectures to improve the effectiveness of face representation. Meanwhile, a multi-branch CNN is constructed to learn features of each cropped patch by the patch strategy and then fuses all the patch features together to form the entire face representation. Compared with the traditional patch methods, their approach has the advantage that no extra space is needed to store the facial patches since the images are cropped online. Moreover, due to the end-to-end training, this approach makes a better use of the interactions between global and local features in the model. Two baseline CNNs (i.e. AlexNet and ResNet) are used to analyse the effectiveness of their method. Experiments show that the proposed system achieves comparable performance with other state-of-the-art methods on the labelled faces in the wild and YouTube face verification tasks. To ensure the reproducibility, the publicly available training set CASIA-WebFace is used.
Starting Page	819
Ending Page	825
Page Count	7
ISSN	17519659
Volume Number	12
e-ISSN	17519667
Issue Number	Issue 5, May (2018)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/12/5
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2017.1085
Journal	IET Image Processing
Publisher Date	2018-01-03
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	AlexNet Baseline CNN CASIA-WebFace Publicly Available Training Set Computer Vision And Image Processing Technique Convolutional Architectures Convolutional Neural Network Deep Face Recognition End-to-end Training Face Recognition Face Representation Feature Extraction Feedforward Neural Network Global Feature Image Fusion Image Recognition Image Representation Local Feature Multibranch CNN Neural Computing Technique Patch Feature Fusion Patch Strategy ResNet Sensor Fusion YouTube Face Verification Task
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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