
title: | FED: An online facial expression dictionary as a first step in the creation of a complete nonverbal dictionary |
author: | Edwin J. de Jongh |
published in: | June 2001 |
appeared as: |
Master of Science thesis Delft University of Technology |
pages | 124 |
PDF (2.824 KB) |

Abstract
A verbal dictionary can be used to look up the spelling of a word, sometimes the phoneme
representation, the meaning in different contexts and rules of transformation. The goal of this
graduation project was to develop a prototype of an online Facial Expression Dictionary, or FED
for short, as a first step in the creation of a complete Nonverbal Dictionary. A complete
Nonverbal Dictionary would contain information about all the ways people communicate with
each other nonverbally. Instead of words, FED contains information about facial expressions.
FED had to become available as a website. The first step in the creation of FED was the
definition of an entry in FED. The choice was made to base each entry in FED on a facial
expression picture generated by a facial expression generation tool called FaceShop. The next
logical step was to implement management facilities, with which the FED entries could be
managed. Subsequently, the FED database was filled with 56 facial expressions.
Essential for a Nonverbal Dictionary is the possibility to issue a nonverbal query through
(multimodal) content. With FED, issuing a nonverbal query is done through uploading a picture
containing a facial expression, after which the user semi-automatically determines the location of
the face and the coordinates of the 30 Facial Characteristics Points or FCP’s of the face model
defined by Kobayashi and Hara. FED then determines the label of the unknown facial expression
by comparing the FCP coordinates to the FCP coordinates of all entries present in the database.
Also, it is possible to let FED determine the la bel of a facial expression sketched with FaceShop.
Other query possibilities have been implemented as well. It is also possible to look for entries in
FED on facial expression label, active Action Units or specific geometrical features. Finally, it is
possible to look for entry incrementally, were the user iteratively selects the facial expression that
resembles the facial expression he is looking for the closest.
The concept of FED as an online Facial Expression Dictionary was tested and found to be a
viable approach. The FED system is easy to use, adapt, extend and manage. The query
possibilities have been tested by a group of 30 students, and although there is room for some
improvement, the results are satisfactory. The approach taken with FED could be used to create a
complete Nonverbal Dictionary.