Title
A Comparison of Human and Machine Learning-based Accuracy for Valence Classification of Subjects in Video Fragments
Author
Holkamp, Y.H.
Schavemaker, J.G.M.
Contributor
Spink, A.J. (editor)
Loijens, L.W.S. (editor)
Woloszynowska-Fraser, M. (editor)
Noldus, L.P.J.J. (editor)
Publication year
2014
Abstract
Facial expressions are the primary way to show one’s emotional state. Automatic recognition of these cues from video using software allows for various improvements in human-computer interaction, ranging from improved feedback for recommender systems to automatic labeling of movies according to the emotions they induce. A number of affective display databases have been created to aid development in this field. These datasets are frequently available for academic use [1, 2, 3], use picture or video stimuli and range from highly controlled [1, 2] to more natural settings [3]. We observe that methods using these datasets report accuracy figures that leave room for improvement [5].
Subject
Communication & Information
MNS - Media & Network Services
TS - Technical Sciences
Infostructures
Image processing
Information Society
Video images
Automatic recognition
Facial expressions
Human computer interaction
To reference this document use:
http://resolver.tudelft.nl/uuid:44d35c22-772d-44a5-9e61-e491577e7dd8
TNO identifier
513946
Source
Measuring Behavior 2014 - 9th International Conference on Methods and Techniques in Behavioral Research, 27-29 August 2014, Wageningen, The Netherlands
Document type
conference paper