
Contents
-
-
-
-
-
-
-
-
Introduction Introduction
-
Human Observer–Based Approaches to Measurement Human Observer–Based Approaches to Measurement
-
Approaches Approaches
-
Message-Based Measurement Message-Based Measurement
-
Sign-Based Measurement Sign-Based Measurement
-
Dimensional Measurement Dimensional Measurement
-
-
Reliability Reliability
-
-
Automated Face Analysis Automated Face Analysis
-
Face and Facial Feature Detection and Tracking Face and Facial Feature Detection and Tracking
-
Registration Registration
-
Feature Extraction Feature Extraction
-
Geometric Features Geometric Features
-
Appearance Features Appearance Features
-
Motion Features Motion Features
-
Data Reduction/Selection Data Reduction/Selection
-
-
Learning Learning
-
Databases Databases
-
-
Applications Applications
-
AU Detection AU Detection
-
Intensity Intensity
-
Physical Pain Physical Pain
-
Depression and Psychological Distress Depression and Psychological Distress
-
Deception Detection Deception Detection
-
Interpersonal Coordination Interpersonal Coordination
-
Expression Transfer Expression Transfer
-
Expression Transfer in Computational Behavioral Science Expression Transfer in Computational Behavioral Science
-
Expression Transfer in Media Arts Expression Transfer in Media Arts
-
-
Other Applications Other Applications
-
Discriminating Between Subtle Differences in Related Expressions Discriminating Between Subtle Differences in Related Expressions
-
Marketing Marketing
-
Drowsy-Driver Detection Drowsy-Driver Detection
-
Instructional Technology Instructional Technology
-
-
User in the Loop User in the Loop
-
-
Discussion Discussion
-
Acknowledgments Acknowledgments
-
References References
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
10 Automated Face Analysis for Affective Computing
Get accessJeffrey Cohn is Professor of Psychology at the University of Pittsburgh and Adjunct Professor at the Robotics Institute, Carnegie Mellon University. He received his PhD in psychology from the University of Massachusetts at Amherst. Dr. Cohn has led interdisciplinary and inter-institutional efforts to develop advanced methods of automatic analysis and synthesis of facial expression and prosody and applied those tools to research in human emotion, interpersonal processes, social development, psychopathology, and affective computing. He co-chairs the ACM International Conference on Multimodal Interfaces (ICMI 2014) and the IEEE International Conference on Automatic Face and Gesture Recognition (FG 2015).
Fernando De la Torre received his B.Sc. degree in Telecommunications, as well as his M.Sc. and Ph. D degrees in Electronic Engineering from La Salle School of Engineering at Ramon Llull University, Barcelona, Spain in 1994, 1996, and 2002, respectively. In 1997 and 2000, he became Assistant and Associate Professor in the Department of Communications and Signal Theory in Enginyeria La Salle. In 2003 he joined the Robotics Institute at Carnegie Mellon University and currently he is Research Associate Professor. His research interests are in the fields of Computer Vision and Machine Learning. Currently, he is directing the Component Analysis Laboratory and the Human Sensing Laboratory.
-
Published:01 July 2014
Cite
Abstract
This chapter is from the forthcoming The Oxford Handbook of Affective Computing edited by Rafael Calvo, Sidney K. D'Mello, Jonathan Gratch, and Arvid Kappas. Facial expression communicates emotion, intention, and physical state; it also regulates interpersonal behavior. Automated face analysis (AFA) for the detection, synthesis, and understanding of facial expression is a vital focus of basic research. While open research questions remain, the field has become sufficiently mature to support initial applications in a variety of areas. We review (1) human observer‒based approaches to measurement that inform AFA; (2) advances in face detection and tracking, feature extraction, registration, and supervised learning; and (3) applications in action unit and intensity detection, physical pain, psychological distress and depression, detection of deception, interpersonal coordination, expression transfer, and other applications. We consider “user in the loop” as well as fully automated systems and discuss open questions in basic and applied research.
Sign in
Personal account
- Sign in with email/username & password
- Get email alerts
- Save searches
- Purchase content
- Activate your purchase/trial code
- Add your ORCID iD
Purchase
Our books are available by subscription or purchase to libraries and institutions.
Purchasing informationMonth: | Total Views: |
---|---|
October 2022 | 9 |
November 2022 | 8 |
December 2022 | 6 |
January 2023 | 4 |
February 2023 | 4 |
March 2023 | 9 |
April 2023 | 2 |
May 2023 | 3 |
June 2023 | 4 |
July 2023 | 2 |
August 2023 | 5 |
September 2023 | 8 |
October 2023 | 7 |
November 2023 | 24 |
December 2023 | 7 |
January 2024 | 2 |
February 2024 | 1 |
March 2024 | 4 |
April 2024 | 15 |
May 2024 | 12 |
June 2024 | 4 |
July 2024 | 3 |
August 2024 | 7 |
September 2024 | 13 |
October 2024 | 9 |
November 2024 | 1 |
December 2024 | 1 |
January 2025 | 3 |
February 2025 | 5 |
March 2025 | 5 |
April 2025 | 4 |
Get help with access
Institutional access
Access to content on Oxford Academic is often provided through institutional subscriptions and purchases. If you are a member of an institution with an active account, you may be able to access content in one of the following ways:
IP based access
Typically, access is provided across an institutional network to a range of IP addresses. This authentication occurs automatically, and it is not possible to sign out of an IP authenticated account.
Sign in through your institution
Choose this option to get remote access when outside your institution. Shibboleth/Open Athens technology is used to provide single sign-on between your institution’s website and Oxford Academic.
If your institution is not listed or you cannot sign in to your institution’s website, please contact your librarian or administrator.
Sign in with a library card
Enter your library card number to sign in. If you cannot sign in, please contact your librarian.
Society Members
Society member access to a journal is achieved in one of the following ways:
Sign in through society site
Many societies offer single sign-on between the society website and Oxford Academic. If you see ‘Sign in through society site’ in the sign in pane within a journal:
If you do not have a society account or have forgotten your username or password, please contact your society.
Sign in using a personal account
Some societies use Oxford Academic personal accounts to provide access to their members. See below.
Personal account
A personal account can be used to get email alerts, save searches, purchase content, and activate subscriptions.
Some societies use Oxford Academic personal accounts to provide access to their members.
Viewing your signed in accounts
Click the account icon in the top right to:
Signed in but can't access content
Oxford Academic is home to a wide variety of products. The institutional subscription may not cover the content that you are trying to access. If you believe you should have access to that content, please contact your librarian.
Institutional account management
For librarians and administrators, your personal account also provides access to institutional account management. Here you will find options to view and activate subscriptions, manage institutional settings and access options, access usage statistics, and more.