research-article

A Lip Localization Algorithm under Variant Light Conditions

Authors:

Yuanyuan LiAuthors Info & Claims

ICMLC '17: Proceedings of the 9th International Conference on Machine Learning and Computing

Pages 305 - 309

https://doi.org/10.1145/3055635.3056587

Published: 24 February 2017 Publication History

Abstract

Lip-reading has potential attractive applications in information security, speech recognition, secret communication and so forth. To build an automatic lip-reading system, one key issue is how to locate the lip region, particularly under variant light condition. Therefore, a new lip localization algorithm is proposed in this paper, which contains three steps: face detection, rough lip localization and precise lip localization. Among them, the precise lip localization algorithm is the main point, which is based on the transformation of YIQ color model and template matching. Compared with the threshold segment based on the color space transformation, template matching is more robust to variant light conditions. Besides, Q component of YIQ color model can further increase the contrast of lip and skin and decrease the effect of illumination. Experimental results demonstrate that the proposed algorithm is efficient and robust in lip localization under variant light conditions.

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Cited By

Chowdhury DKumari RBakshi SSahoo MDas A(2022)Lip as biometric and beyond: a surveyMultimedia Tools and Applications10.1007/s11042-021-11613-581:3(3831-3865)Online publication date: 1-Jan-2022
https://dl.acm.org/doi/10.1007/s11042-021-11613-5
Liu XCheung Y(2017)On incremental collaborative appearance model and regional particle filtering for lip region trackingIntegrated Computer-Aided Engineering10.3233/ICA-17055725:1(63-80)Online publication date: 1-Jan-2017
https://dl.acm.org/doi/10.3233/ICA-170557

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ICMLC '17: Proceedings of the 9th International Conference on Machine Learning and Computing

February 2017

545 pages

ISBN:9781450348171

DOI:10.1145/3055635

Copyright © 2017 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 the author(s) 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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Southwest Jiaotong University

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Association for Computing Machinery

New York, NY, United States

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Published: 24 February 2017

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ICMLC 2017: 2017 the 9th International Conference on Machine Learning and Computing

February 24 - 26, 2017

Singapore, Singapore

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Cited By

Chowdhury DKumari RBakshi SSahoo MDas A(2022)Lip as biometric and beyond: a surveyMultimedia Tools and Applications10.1007/s11042-021-11613-581:3(3831-3865)Online publication date: 1-Jan-2022
https://dl.acm.org/doi/10.1007/s11042-021-11613-5
Liu XCheung Y(2017)On incremental collaborative appearance model and regional particle filtering for lip region trackingIntegrated Computer-Aided Engineering10.3233/ICA-17055725:1(63-80)Online publication date: 1-Jan-2017
https://dl.acm.org/doi/10.3233/ICA-170557

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