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research-article

Recognizing Human Facial Expressions From Long Image Sequences Using Optical Flow

Authors:

Larry S. DavisAuthors Info & Claims

IEEE Transactions on Pattern Analysis and Machine Intelligence, Volume 18, Issue 6

Pages 636 - 642

https://doi.org/10.1109/34.506414

Published: 01 June 1996 Publication History

Abstract

An approach to the analysis and representation of facial dynamics for recognition of facial expressions from image sequences is presented. The algorithms utilize optical flow computation to identify the direction of rigid and nonrigid motions that are caused by human facial expressions. A mid-level symbolic representation motivated by psychological considerations is developed. Recognition of six facial expressions, as well as eye blinking, is demonstrated on a large set of image sequences.

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Cited By

Yildirim SChimeumanu MRana Z(2023)The influence of micro-expressions on deception detectionMultimedia Tools and Applications10.1007/s11042-023-14551-682:19(29115-29133)Online publication date: 16-Mar-2023
https://dl.acm.org/doi/10.1007/s11042-023-14551-6
Pise AAlqahtani MVerma PK PKarras DS PHalifa A(2022)Methods for Facial Expression Recognition with Applications in Challenging SituationsComputational Intelligence and Neuroscience10.1155/2022/92614382022Online publication date: 1-Jan-2022
https://dl.acm.org/doi/10.1155/2022/9261438
Sarma DBhuyan M(2021)Methods, Databases and Recent Advancement of Vision-Based Hand Gesture Recognition for HCI Systems: A ReviewSN Computer Science10.1007/s42979-021-00827-x2:6Online publication date: 29-Aug-2021
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Index Terms

Recognizing Human Facial Expressions From Long Image Sequences Using Optical Flow
1. Computing methodologies

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Information

Published In

cover image IEEE Transactions on Pattern Analysis and Machine Intelligence

IEEE Transactions on Pattern Analysis and Machine Intelligence Volume 18, Issue 6

June 1996

96 pages

ISSN:0162-8828

Editor:
Rangachar Kasturi
The Pennsylvania State Univ., University Park

Issue’s Table of Contents

Copyright © Copyright © 1996 IEEE. All Rights Reserved.

Publisher

IEEE Computer Society

United States

Publication History

Published: 01 June 1996

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Cited By

Yildirim SChimeumanu MRana Z(2023)The influence of micro-expressions on deception detectionMultimedia Tools and Applications10.1007/s11042-023-14551-682:19(29115-29133)Online publication date: 16-Mar-2023
https://dl.acm.org/doi/10.1007/s11042-023-14551-6
Pise AAlqahtani MVerma PK PKarras DS PHalifa A(2022)Methods for Facial Expression Recognition with Applications in Challenging SituationsComputational Intelligence and Neuroscience10.1155/2022/92614382022Online publication date: 1-Jan-2022
https://dl.acm.org/doi/10.1155/2022/9261438
Sarma DBhuyan M(2021)Methods, Databases and Recent Advancement of Vision-Based Hand Gesture Recognition for HCI Systems: A ReviewSN Computer Science10.1007/s42979-021-00827-x2:6Online publication date: 29-Aug-2021
https://dl.acm.org/doi/10.1007/s42979-021-00827-x
Raychaudhuri SManjunath SSrinivasan CSwathi NSushma SNitin Bhushan KNarendra Babu C(2021)Prescriptive analytics for impulsive behaviour prevention using real-time biometricsProgress in Artificial Intelligence10.1007/s13748-020-00229-910:2(99-112)Online publication date: 1-Jun-2021
https://dl.acm.org/doi/10.1007/s13748-020-00229-9
Yang HYin L(2019)Learning Temporal Information From A Single Image For AU Detection2019 14th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2019)10.1109/FG.2019.8756556(1-8)Online publication date: 14-May-2019
https://dl.acm.org/doi/10.1109/FG.2019.8756556
Jaiswal SVirmani SSethi VDe KRoy P(2019)An intelligent recommendation system using gaze and emotion detectionMultimedia Tools and Applications10.1007/s11042-018-6755-178:11(14231-14250)Online publication date: 1-Jun-2019
https://dl.acm.org/doi/10.1007/s11042-018-6755-1
Yim SSung CMiyashita SRus DKim S(2018)Animatronic soft robots by additive foldingInternational Journal of Robotics Research10.1177/027836491877202337:6(611-628)Online publication date: 1-May-2018
https://dl.acm.org/doi/10.1177/0278364918772023
Chrysos GAntonakos ESnape PAsthana AZafeiriou S(2018)A Comprehensive Performance Evaluation of Deformable Face Tracking "In-the-Wild"International Journal of Computer Vision10.1007/s11263-017-0999-5126:2-4(198-232)Online publication date: 1-Apr-2018
https://dl.acm.org/doi/10.1007/s11263-017-0999-5
Zhou TBhaskar HLiu FYang JCai P(2017)Online learning and joint optimization of combined spatial-temporal models for robust visual trackingNeurocomputing10.1016/j.neucom.2016.11.055226:C(221-237)Online publication date: 22-Feb-2017
https://dl.acm.org/doi/10.1016/j.neucom.2016.11.055
Liu MShan SWang RChen X(2016)Learning Expressionlets via Universal Manifold Model for Dynamic Facial Expression RecognitionIEEE Transactions on Image Processing10.1109/TIP.2016.261542425:12(5920-5932)Online publication date: 1-Dec-2016
https://dl.acm.org/doi/10.1109/TIP.2016.2615424
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