Feature-point tracking by optical flow discriminates subtle differences in facial expression

Jeffrey F. Cohn, James Jenn-Jier Lien, Adena J. Zlochower, Takeo Kanade

Research output: Chapter in Book/Report/Conference proceedingConference contribution

92 Citations (Scopus)

Abstract

Current approaches to automated analysis have focused an a small set of prototypic expressions (e.g. joy or anger). Prototypic expressions occur infrequently in everyday life, however, and emotion expression is far more varied. To capture the full range of emotion expression, automated discrimination of fine grained changes in facial expression is needed. We developed and implemented an optical flow based approach (feature point tracking) that is sensitive to subtle changes in facial expression. In image sequences from 100 young adults, action units and action unit combinations in the brow and mouth regions were selected for analysis if they occurred a minimum of 25 times in the image database. Selected facial features were automatically tracked using a hierarchical algorithm for estimating optical flow. Image sequences were randomly divided into training and test sets. Feature point tracking demonstrated high concurrent validity with human coding using the Facial Action Coding System (FACS).

Original languageEnglish
Title of host publicationProceedings - 3rd IEEE International Conference on Automatic Face and Gesture Recognition, FG 1998
PublisherIEEE Computer Society
Pages396-401
Number of pages6
ISBN (Print)0818683449, 9780818683442
DOIs
Publication statusPublished - 1998 Jan 1
Event3rd IEEE International Conference on Automatic Face and Gesture Recognition, FG 1998 - Nara, Japan
Duration: 1998 Apr 141998 Apr 16

Publication series

NameProceedings - 3rd IEEE International Conference on Automatic Face and Gesture Recognition, FG 1998

Other

Other3rd IEEE International Conference on Automatic Face and Gesture Recognition, FG 1998
CountryJapan
CityNara
Period98-04-1498-04-16

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition

Fingerprint Dive into the research topics of 'Feature-point tracking by optical flow discriminates subtle differences in facial expression'. Together they form a unique fingerprint.

Cite this