Wei, Haolin, Scanlon, Patricia, Li, Yingbo, Monaghan, David ORCID: 0000-0002-5169-9902 and O'Connor, Noel E. ORCID: 0000-0002-4033-9135 (2013) Real-time head nod and shake detection for continuous human affect recognition. In: Image Analysis for Multimedia Interactive Services (WIAMIS), 2013, 3-5 July 2013, Paris, France.
Abstract
Human affect recognition is the field of study associated with using automatic techniques to identify human emotion or human affective state. A person’s affective states is often communicated non-verbally through body language. A large part of human body language communication is the use of head gestures. Almost all cultures use subtle head movements to convey meaning. Two of the most common and distinct head gestures are the head nod and the head shake gestures. In this paper we present a robust system to automatically detect head nod and shakes. We employ the Microsoft Kinect and utilise discrete Hidden Markov Models (HMMs) as the backbone to a to a machine learning based classifier within the system. The system achieves 86% accuracy on test datasets and results are provided.
Metadata
Item Type: | Conference or Workshop Item (Paper) |
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Event Type: | Conference |
Refereed: | Yes |
Uncontrolled Keywords: | Human affect recognition; Non-verbal communication; Body language; Gesture recognition |
Subjects: | Computer Science > Machine learning Computer Science > Artificial intelligence |
DCU Faculties and Centres: | Research Institutes and Centres > INSIGHT Centre for Data Analytics DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing Research Institutes and Centres > CLARITY: The Centre for Sensor Web Technologies |
Use License: | This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License |
ID Code: | 19586 |
Deposited On: | 17 Oct 2013 10:07 by David Monaghan . Last Modified 04 Feb 2020 15:14 |
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