Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/67493
Title: Feature-aging for age-invariant face recognition
Authors: Zhou, H
Wong, KW
Lam, KM 
Issue Date: 2015
Source: 2015 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA), Hong Kong, China, 16-19 Dec 2015, p.1161-1165
Abstract: Age-invariant face recognition has attracted some recent attention. In real applications, the age progression of those face images, stored in a face database for recognition and identification purposes, should also be considered, so as to achieve a higher accuracy level. In this paper, we propose a method to predict the aging of facial features so as to alleviate the effect of age progression on face recognition. The original facial feature and the aged facial feature of a face image should be correlated, so they are fused by using canonical correlation analysis to form a coherent feature for face recognition. The performance of our proposed approach is evaluated based on the FGNet database, and compared to some existing face recognition algorithms. Experiment results show that our proposed method can achieve a superior performance, when the query and probe face images have a large age difference.
Keywords: Face
Face recognition
Training
Feature extraction
Facial features
Aging
Correlation
Publisher: Institute of Electrical and Electronics Engineers
ISBN: 978-9-8814-7680-7 (electronic)
978-1-4673-9593-9 (print on demand(PoD))
DOI: 10.1109/APSIPA.2015.7415454
Appears in Collections:Conference Paper

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