NDLI: Multi-directional local adjacency descriptors (MDLAD) for heterogeneous face recognition

Content Provider	IET Digital Library
Author	Bhattacharya, Shubhobrata Dasgupta, Anirban Routray, Aurobinda
Abstract	This paper presents new image descriptors for heterogeneous face recognition (HFR). The proposed descriptors combine directional and neighborhood information using a rotating spoke and concentric rings concept. We name the descriptors as multi-directional local adjacency descriptors (MDLAD). This family of descriptor captures the directional information through successive rotations of a pair of orthogonal spokes. Likewise, they capture the adjacency information through a comparison against the central pixel of a window with concentric rings around the central pixel. The MDLAD is found to describe the face images well for recognition purposes, which when matched using the chi-squared distance. The face recognition performance with MDLAD improves with its use as a layer in a deep neural network, which yields a robust classification for heterogeneous face recognition with respect to the state-of-the-art methods. The MDLADNET deep network is easily trainable with few hyperparameters and limited data samples as compared to existing similar deep networks. We have experimented on different heterogeneous modalities viz. Extended Yale B, CASIA, CUFSF, IIITD, LFW, Multi-PIE, and CARL, and have found proficient results.
Starting Page	982
Ending Page	994
Page Count	13
ISSN	17519659
Volume Number	14
e-ISSN	17519667
Issue Number	Issue 5, Apr (2020)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/14/5
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2019.0199
Journal	IET Image Processing
Publisher Date	2019-12-24
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Adjacency Information CARL CASIA Central Pixel Computer Vision And Image Processing Technique Concentric Rings Concept Convolutional Neural Nets CUHK Face Sketch Deep Convolutional Neural Network Directional Information Extended Yale B Face Recognition Feature Extraction Heterogeneous Face Recognition Heterogeneous Face Representation Heterogeneous Modalities IIITD Image Descriptors Image Recognition Image Representation LFW Multi-PIE Multidirectional Local Adjacency Descriptors Neighbourhood Information Neural Computing Technique Rotating Spoke
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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