Journal article
Towards Generic Modelling of Viewer Interest Using Facial Expression and Heart Rate Features
IEEE Access, Vol.6, pp.62490-62502
14/11/2018
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Source: InCites
Abstract
Automatic detection of viewer interest while watching video contents can enable multimedia applications, such as online video streaming, to recommend contents in real time. However, there is yet a generic model for detecting viewer interest that is independent of subject and content while using noninvasive sensors in near-natural settings. This paper is the first attempt at solving this issue by investigating the feasibility of a generic model for detecting viewer interest based on facial expression and heart rate features. The proposed model adopts deep learning features, which are trained and tested using multisubjects' data across different video stimuli domains. The experimental results show that the generic model can reach a similar accuracy to a domain-specific model.
Details
- Title
- Towards Generic Modelling of Viewer Interest Using Facial Expression and Heart Rate Features
- Creators
- Prithwi Raj Chakraborty - Southern Cross UniversityDian Wirawan Tjondronegoro - Southern Cross UniversityLigang Zhang - Central Queensland UniversityVinod Chandran - Queensland University of Technology
- Publication Details
- IEEE Access, Vol.6, pp.62490-62502
- Publisher
- Institute of Electrical and Electronics Engineers
- Grant note
- Queensland University of Technology (10.13039/501100001793)
- Identifiers
- 991012926972202368
- Copyright
- Copyright © 2018 IEEE. Translations and content mining are permitted for academic research only. Personal use is also permitted, but republication/redistribution requires IEEE permission. See http://www.ieee.org/publications_standards/publications/rights/index.html for more information.
- Academic Unit
- School of Business and Tourism; Faculty of Science and Engineering; Information Technology
- Language
- English
- Resource Type
- Journal article