extended-abstract

Expression analysis in the wild: from individual to groups

Author:

Abhinav DhallAuthors Info & Claims

ICMR '13: Proceedings of the 3rd ACM conference on International conference on multimedia retrieval

Pages 325 - 328

https://doi.org/10.1145/2461466.2461529

Published: 16 April 2013 Publication History

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Abstract

With the advances in the computer vision in the past few years, analysis of human facial expressions has gained attention. Facial expression analysis is now an active field of research for over two decades now. However, still there are a lot of questions unanswered. This project will explore and devise algorithms and techniques for facial expression analysis in practical environments. Methods will also be developed for inferring the emotion of a group of people. The central hypothesis of the project is that close to real-world data can be extracted from movies and facial expression analysis on movies is a stepping stone for moving to analysis in the real-world. For the analysis of groups of people various attributes effect the perception of mood. A system which can classify the mood of a group of people in videos will be developed and will be used to solve the problem of efficient image browsing and retrieval based on emotion.

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Cited By

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Zhang FMao QShen XZhan YDong M(2018)Spatially Coherent Feature Learning for Pose-Invariant Facial Expression RecognitionACM Transactions on Multimedia Computing, Communications, and Applications10.1145/317664614:1s(1-19)Online publication date: 6-Mar-2018
https://dl.acm.org/doi/10.1145/3176646
Mao QRao QYu YDong M(2017)Hierarchical Bayesian Theme Models for Multipose Facial Expression RecognitionIEEE Transactions on Multimedia10.1109/TMM.2016.262928219:4(861-873)Online publication date: 1-Apr-2017
https://dl.acm.org/doi/10.1109/TMM.2016.2629282

Index Terms

Expression analysis in the wild: from individual to groups
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
  2. Computer graphics
    1. Image manipulation
      1. Image processing

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Information

Published In

ICMR '13: Proceedings of the 3rd ACM conference on International conference on multimedia retrieval

April 2013

362 pages

ISBN:9781450320337

DOI:10.1145/2461466

General Chairs:
Ramesh Jain
University of California, Irvine, USA
,
Balakrisknan Prabhakaran
University of Texas at Dallas, USA
,
Program Chairs:
Marcel Worring
University of Amsterdam, The Netherlands
,
John Smith
IBM Research, New York, USA
,
Tat-Seng Chua
National University of Singapore

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

New York, NY, United States

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Published: 16 April 2013

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SIGMM

ICMR'13: International Conference on Multimedia Retrieval

April 16 - 20, 2013

Texas, Dallas, USA

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ICMR '13 Paper Acceptance Rate 38 of 96 submissions, 40%;

Overall Acceptance Rate 254 of 830 submissions, 31%

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Cited By

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Zhang FMao QShen XZhan YDong M(2018)Spatially Coherent Feature Learning for Pose-Invariant Facial Expression RecognitionACM Transactions on Multimedia Computing, Communications, and Applications10.1145/317664614:1s(1-19)Online publication date: 6-Mar-2018
https://dl.acm.org/doi/10.1145/3176646
Mao QRao QYu YDong M(2017)Hierarchical Bayesian Theme Models for Multipose Facial Expression RecognitionIEEE Transactions on Multimedia10.1109/TMM.2016.262928219:4(861-873)Online publication date: 1-Apr-2017
https://dl.acm.org/doi/10.1109/TMM.2016.2629282

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Recognizing action units for facial expression analysis

Recognizing Action Units for Facial Expression Analysis

Context Based Facial Expression Analysis in the Wild

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