NDLI: Robust partial face recognition using instance-to-class distance

Content Provider	IEEE Xplore Digital Library
Author	Junlin Hu Jiwen Lu Yap-Peng Tan
Copyright Year	2013
Description	Author affiliation: Sch. of Electr. & Electron. Eng., Nanyang Technol. Univ., Singapore, Singapore (Junlin Hu; Yap-Peng Tan) \|\| Adv. Digital Sci. Center, Singapore, Singapore (Jiwen Lu)
Abstract	We present a new face recognition approach from partial face patches by using an instance-to-class distance. While numerous face recognition methods have been proposed over the past two decades, most of them recognize persons from whole face images. In many real world applications, partial faces usually occur in unconstrained scenarios such as visual surveillance systems. Hence, it is very important to recognize an arbitrary facial patch to enhance the intelligence of such systems. In this paper, we develop a robust partial face recognition approach based on local feature representation, where the similarity between each probe patch and gallery face is computed by using the instance-to-class distance with the sparse constraint. Experiments on two popular face datasets are presented to show the efficacy of our proposed method.
Starting Page	1
Ending Page	6
File Size	1334393
Page Count	6
File Format	PDF
e-ISBN	9781479902903
DOI	10.1109/VCIP.2013.6706353
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-11-17
Publisher Place	Malaysia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image recognition Accuracy Face recognition Partial face recognition Occluded face Feature extraction Robustness Instance-to-class distance Face Probes
Content Type	Text
Resource Type	Article

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