Evolving an emotion recognition module for an intelligent agent using genetic programming and a genetic algorithm
Created by W.Langdon from
gp-bibliography.bib Revision:1.8129
- @Article{DBLP:journals/alr/YusufSTS16,
-
author = "Rahadian Yusuf and Dipak Gaire Sharma and
Ivan Tanev and Katsunori Shimohara",
-
title = "Evolving an emotion recognition module for an
intelligent agent using genetic programming and a
genetic algorithm",
-
journal = "Artificial Life and Robotics",
-
volume = "21",
-
number = "1",
-
pages = "85--90",
-
year = "2016",
-
month = mar,
-
keywords = "genetic algorithms, genetic programming, Emotion
recognition, Facial expression, Gestures",
-
URL = "https://rdcu.be/cIJ4u",
-
URL = "https://doi.org/10.1007/s10015-016-0263-z",
-
DOI = "doi:10.1007/s10015-016-0263-z",
-
timestamp = "Thu, 26 Nov 2020 00:00:00 +0100",
-
biburl = "https://dblp.org/rec/journals/alr/YusufSTS16.bib",
-
bibsource = "dblp computer science bibliography, https://dblp.org",
-
size = "6 pages",
-
abstract = "Most studies use the facial expression to recognize a
users emotion; however, gestures, such as nodding,
shaking the head, or stillness can also be indicators
of the users emotion. In our research, we use the
facial expression and gestures to detect and recognize
a user emotion. The pervasive Microsoft Kinect sensor
captures video data, from which several features
representing facial expressions and gestures are
extracted. An in-house extensible markup language-based
genetic programming engine (XGP) evolves the emotion
recognition module of our system. To improve the
computational performance of the recognition module, we
implemented and compared several approaches, including
directed evolution, collaborative filtering via
canonical voting, and a genetic algorithm, for an
automated voting system. The experimental results
indicate that XGP is feasible for evolving emotion
classifiers. In addition, the obtained results verify
that collaborative filtering improves the generality of
recognition. From a psychological viewpoint, the
results prove that different people might express their
emotions differently, as the emotion classifiers that
are evolved for particular users might not be applied
successfully to other user(s).",
- }
Genetic Programming entries for
Rahadian Yusuf
Dipak Gaire Sharma
Ivan T Tanev
Katsunori Shimohara
Citations