Gesture-based affect modeling for intelligent tutoring systems
College
College of Computer Studies
Department/Unit
Software Technology
Document Type
Conference Proceeding
Source Title
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume
6738 LNAI
First Page
426
Last Page
428
Publication Date
6-23-2011
Abstract
This paper investigates the feasibility of using gestures and posture for building affect models for an ITS. Recordings of students studying with a computer were taken and an HMM was built to recognize gestures and posture. Results indicate distinctions can be achieved with an accuracy of 43.10% using leave-one out cross validation. Results further indicate the relevance of hand location, movement and speed of movement as features for affect modeling using gestures and posture. © 2011 Springer-Verlag Berlin Heidelberg.
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Digitial Object Identifier (DOI)
10.1007/978-3-642-21869-9_58
Recommended Citation
Bustos, D., Chua, G., Cruz, R., Santos, J., & Suarez, M. (2011). Gesture-based affect modeling for intelligent tutoring systems. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 6738 LNAI, 426-428. https://doi.org/10.1007/978-3-642-21869-9_58
Disciplines
Computer Sciences
Keywords
Affect (Psychology); Gesture; Pattern recognition systems; Intelligent tutoring systems
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