research-article

Face verification with aging using AdaBoost and local binary patterns

Authors:

Gayathri Mahalingam,

Chandra KambhamettuAuthors Info & Claims

ICVGIP '10: Proceedings of the Seventh Indian Conference on Computer Vision, Graphics and Image Processing

Pages 101 - 108

https://doi.org/10.1145/1924559.1924573

Published: 12 December 2010 Publication History

Abstract

In this paper, we study the face verification task across age by constructing a simple but powerful representation of the face which uses Local Binary Pattern (LBP) histograms. The spatial information is incorporated by constructing a hierarchical representation of the face image and computing the LBP histogram at each level. A set of most discriminative LBP features of the face are extracted using the AdaBoost learning algorithm. A strong classifier is built using a set of weak classifiers extracted and is used for classification purposes. Several experiments on the FGnet and the MORPH database were performed and the results indicate a significant improvement in the performance when compared with other discriminative approaches. Performance improvement is achieved with smaller age gaps between image pairs and it stabilizes as the age gap increases. Also, the facial hair, glasses, etc. provide discriminative cues to the system in face verification.

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Face verification with aging using AdaBoost and local binary patterns

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cover image ACM Other conferences

ICVGIP '10: Proceedings of the Seventh Indian Conference on Computer Vision, Graphics and Image Processing

December 2010

533 pages

ISBN:9781450300605

DOI:10.1145/1924559

General Chairs:
Rama Chellappa
University of Maryland
,
Padmanabhan Anandan
Microsoft Research, India
,
Program Chairs:
A. N. Rajagopalan
Indian Institute of Technology Madras, India
,
P. J. Narayanan
International Institute of Information Technology Hyderabad, India
,
Philip Torr
Oxford Brookes University, UK

Copyright © 2010 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

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Publication History

Published: 12 December 2010

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ICVGIP '10

ICVGIP '10: Seventh Indian Conference on Computer Vision, Graphics and Image Processing

December 12 - 15, 2010

Chennai, India

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Overall Acceptance Rate 95 of 286 submissions, 33%

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Yuan YTang CXia SChen ZQi T(2020)HandNetProceedings of the 2020 4th International Conference on Vision, Image and Signal Processing10.1145/3448823.3448838(1-6)Online publication date: 9-Dec-2020
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Ginoya SPrajapati HDabhi V(2020)Survey on Cross-Age Face Comparison2020 6th International Conference on Advanced Computing and Communication Systems (ICACCS)10.1109/ICACCS48705.2020.9074389(445-451)Online publication date: Mar-2020
https://doi.org/10.1109/ICACCS48705.2020.9074389
Kamarajugadda KMovva P(2019)Periocular Region Based Biometric Identification Using SIFT and SURF Key Point Descriptors2019 IEEE 10th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON)10.1109/IEMCON.2019.8936271(0968-0972)Online publication date: Oct-2019
https://doi.org/10.1109/IEMCON.2019.8936271
Kishore Kumar KPavani M(2018)Periocular Region-Based Biometric Identification Using Local Binary Pattern and Its VariantsInformation and Communication Technology for Competitive Strategies10.1007/978-981-13-0586-3_57(581-590)Online publication date: 31-Aug-2018
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Kishore Kumar KTrinatha Rao P(2018)Periocular Region Based Biometric Identification Using the Local DescriptorsIntelligent Computing and Information and Communication10.1007/978-981-10-7245-1_34(341-351)Online publication date: 20-Jan-2018
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Kishore Kumar KTrinatha Rao P(2016)Face Verification Across Ages Using Discriminative Methods and See 5.0 ClassifierProceedings of First International Conference on Information and Communication Technology for Intelligent Systems: Volume 210.1007/978-3-319-30927-9_43(439-448)Online publication date: 4-May-2016
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Zhai HLiu CDong HJi YGuo YGong S(2015)Face Verification Across Aging Based on Deep Convolutional Networks and Local Binary PatternsIntelligence Science and Big Data Engineering. Image and Video Data Engineering10.1007/978-3-319-23989-7_35(341-350)Online publication date: 22-Oct-2015
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