Abstract
Social signals and interpretation of carried information is of high importance in Human Computer Interaction. Often used for affect recognition, the cues within these signals are displayed in various modalities. Fusion of multi-modal signals is a natural and interesting way to improve automatic classification of emotions transported in social signals. Throughout most present studies, uni-modal affect recognition as well as multi-modal fusion, decisions are forced for fixed annotation segments across all modalities. In this paper, we investigate the less prevalent approach of event driven fusion, which indirectly accumulates asynchronous events in all modalities for final predictions. We present a fusion approach, handling short-timed events in a vector space, which is of special interest for real-time applications. We compare results of segmentation based uni-modal classification and fusion schemes to the event driven fusion approach. The evaluation is carried out via detection of enjoyment-episodes within the audiovisual Belfast Story-Telling Corpus.
Original language | English |
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Title of host publication | MM '14 Proceedings of the 22nd ACM International Conference on Multimedia |
Publisher | Association for Computing Machinery |
Pages | 377-386 |
Number of pages | 10 |
ISBN (Print) | 9781450330633 |
DOIs | |
Publication status | Published - 03 Nov 2014 |
Event | 2014 ACM Conference on Multimedia, MM 2014 - Orlando, United States Duration: 03 Nov 2014 → 07 Nov 2014 |
Conference
Conference | 2014 ACM Conference on Multimedia, MM 2014 |
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Country/Territory | United States |
City | Orlando |
Period | 03/11/2014 → 07/11/2014 |
Keywords
- Affect recognition
- Event-driven fusion
- Multi-modal fusion
- Social signal processing
ASJC Scopus subject areas
- Computer Graphics and Computer-Aided Design
- Computer Vision and Pattern Recognition
- Media Technology
- Software