liu.seSearch for publications in DiVA
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Measurement of JND Thresholds and Riemannian Geometry in Facial Expression Space
Chuo Univ, Japan.
Linköping University, Department of Science and Technology, Media and Information Technology. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV).ORCID iD: 0000-0001-7557-4904
Chuo Univ, Japan.
2018 (English)In: HUMAN-COMPUTER INTERACTION: THEORIES, METHODS, AND HUMAN ISSUES, HCI INTERNATIONAL 2018, PT I, SPRINGER INTERNATIONAL PUBLISHING AG , 2018, Vol. 10901, p. 453-464Conference paper, Published paper (Refereed)
Abstract [en]

Currently the most popular approach to facial expression analysis uses categorical representations of expressions based on labels like sad, happy and angry. Subtle expression variations require however a quantitative and continuous representation. Besides, todays subjective expression spaces, built by semantic differential level scores and reduced to low dimensional continuous spaces using MDS or PCA have no direct correspondence with the physical stimuli or the expression images. On the other hand, the spaces used in engineering are based on purely physical stimuli or images which can hardly be called expression spaces. Even in models incorporating spacial structure, the geometry of the expression space received little attention and is usually assumed to be Euclidean. The aim of this paper is to build an expression space which is directly connected with the physical stimuli or the expression images. At the same time, it has to incorporate the subjective characteristics of expression perception. We use methods from psychophysics to build an expression space based on the physical stimuli or expression image space equipped with JND or discrimination threshold data. The construction follows the approach used in color science where the MacAdam ellipsoids provide for every color a metric tensor in a Riemannian space. We show that the discrimination thresholds indicate that the space is not Non- Euclidean. We will also illustrate the intrinsic geometrical structure of the expression spaces for several observers obtained from two large image databases of face expressions.

Place, publisher, year, edition, pages
SPRINGER INTERNATIONAL PUBLISHING AG , 2018. Vol. 10901, p. 453-464
Series
Lecture Notes in Computer Science, ISSN 0302-9743
Keywords [en]
Facial expressions; Emotions; Categorical theory; Dimensional theory; JND thresholds; Riemannian geometry
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
URN: urn:nbn:se:liu:diva-153415DOI: 10.1007/978-3-319-91238-7_37ISI: 000450991000037ISBN: 978-3-319-91238-7 (electronic)ISBN: 978-3-319-91237-0 (print)OAI: oai:DiVA.org:liu-153415DiVA, id: diva2:1271477
Conference
20th International Conference on Human-Computer Interaction (HCI International)
Available from: 2018-12-17 Created: 2018-12-17 Last updated: 2018-12-17

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full text

Search in DiVA

By author/editor
Lenz, Reiner
By organisation
Media and Information TechnologyFaculty of Science & EngineeringCenter for Medical Image Science and Visualization (CMIV)
Computer Vision and Robotics (Autonomous Systems)

Search outside of DiVA

GoogleGoogle Scholar

doi
isbn
urn-nbn

Altmetric score

doi
isbn
urn-nbn
Total: 9 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf