skip to main content
10.1145/3267305.3274139acmconferencesArticle/Chapter ViewAbstractPublication PagesubicompConference Proceedingsconference-collections
abstract

Ubiquitous Emotion Recognition with Multimodal Mobile Interfaces

Published:08 October 2018Publication History

ABSTRACT

In 1997 Rosalind Picard introduced fundamental concepts of affect recognition [1]. Since this time, multimodal interfaces such as Brain-computer interfaces (BCIs), RGB and depth cameras, physiological wearables, multimodal facial data and physiological data have been used to study human emotion. Much of the work in this field focuses on a single modality to recognize emotion. However, there is a wealth of information that is available for recognizing emotions when incorporating multimodal data. Considering this, the aim of this workshop is to look at current and future research activities and trends for ubiquitous emotion recognition through the fusion of data from various multimodal, mobile devices.

References

  1. R. Picard, 1997. Affective Computing. MIT press Cambridge, Vol. 252. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. S. Sgaosough et al. 2016. Emotion Recognition Using Mobile Phones. Intl. Conf. on e-Health Networking, Applications, and Services.Google ScholarGoogle Scholar
  3. G. Chittaranjan et al. 2011. Who's who with big-five: Analyzing and classifying personality traits with smartphones. 15th Annual Intl. Symp. On Wearable Computers (pp. 53--60). IEEE Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. Y.-A. de Montjoye et al. 2013. Predicting personality using novel mobile phone-based metrics. Intl. Conf. on Soc. Comput., Behav.-Cultural Model., and Predict. Springer (pp. 48--55). Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. K. Rachuri et al. 2010. EmotionSense: a mobile phone based adaptive platform for experimental social psychology research. 12th International Conference on Ubiquitous Computing (pp. 281--290). ACM. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. H. Lee et al. 2012. Towards unobtrusive emotion recognition for affective social communication. Consumer Communications for Networking Conference (pp. 260--254). IEEE.Google ScholarGoogle ScholarCross RefCross Ref
  7. A. Bogomolov et al. 2014. Daily stress rec. from mobile phone data, weather cond., and individual traits. 22nd Intl. Conf. on Mult. (pp. 477--486). ACM. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Z. Zhang et al. 2016. Multimodal Spontaneous Emotion Corpus for Human Behavior Analysis. Computer Vision and Pattern Recognition.Google ScholarGoogle Scholar
  9. X. Zhang et al. 2014. BP4D-Spontaneous: A high resolution spontaneous 3D dynamic facial expression database. Image and Vision Computing.Google ScholarGoogle Scholar
  10. X. Zhang et al. 2013. A high-resolution spontaneous 3D dynamic facial expression database. Face and Gesture Recognition.Google ScholarGoogle Scholar
  11. C. Mühl, G. Chanel, B. Allison, A. Nijholt. A survey of affective brain computer interfaces: principles, state-of-the-art, and challenges. Brain-Computer Interfaces, Vol. 1, Issue 2, Taylor & Francis, Oxford, UK, ISSN 2326-263X, 2014, 66--84.Google ScholarGoogle Scholar
  12. Nijholt, A. (2015, December). Multi-modal and multi-brain-computer interfaces: A review. Info., Comm. and Signal Processing (ICICS), 2015 10th International Conference on (pp. 1--5). IEEE.Google ScholarGoogle Scholar
  13. De la Torre et al. 2011. Facial expression analysis. Visual Analysis of Human (pp. 377--409).Google ScholarGoogle Scholar
  14. Y-I. Tian et al. 2001. Recognizing action units for facial expression analysis. Transactions on Pattern Analysis and Machine Intelligence (pp. 97--115). IEEE. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. R. Picard. 2001. Toward machine emotional intelligence. Transactions on Pattern Analysis and Machine Intelligence (pp. 1175--1191). IEEE. Google ScholarGoogle ScholarDigital LibraryDigital Library

Recommendations

Comments

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Sign in
  • Published in

    cover image ACM Conferences
    UbiComp '18: Proceedings of the 2018 ACM International Joint Conference and 2018 International Symposium on Pervasive and Ubiquitous Computing and Wearable Computers
    October 2018
    1881 pages
    ISBN:9781450359665
    DOI:10.1145/3267305

    Copyright © 2018 Owner/Author

    Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.

    Publisher

    Association for Computing Machinery

    New York, NY, United States

    Publication History

    • Published: 8 October 2018

    Check for updates

    Qualifiers

    • abstract
    • Research
    • Refereed limited

    Acceptance Rates

    Overall Acceptance Rate764of2,912submissions,26%

    Upcoming Conference

PDF Format

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader