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Proceedings of the 3rd ACM international workshop on Audio/visual emotion challenge (AVEC '13)
| Content Provider | ACM Digital Library |
|---|---|
| Editor | Cohn, Jeff Valstar, Michel Cowie, Roddy Eyben, Florian Krajewski, Jarek Pantic, Maja Schuller, Björn |
| Copyright Year | 2013 |
| Abstract | It is our great pleasure to welcome you to the 3d Audio-Visual Emotion recognition Challenge (AVEC 2013), held in conjunction with the ACM Multimedia 2013. This year's challenge and associated workshop continues to push the boundaries of audio-visual emotion recognition. The first AVEC challenge posed the problem of detecting discrete emotion classes on an extremely large set of natural behaviour data. The second AVEC extended this problem to the prediction of continuous valued dimensional affect on the same set of challenging data. Now, in its third edition, we have extended the problem even further to include the prediction of self-reported severity of depression, which is a frequently occurring mood disorder. The mission of the AVEC challenge and workshop series is to provide a common benchmark test set for individual multimodal information processing and to bring together the audio and video emotion recognition communities, to compare the relative merits of the two approaches to emotion recognition under well-defined and strictly comparable conditions and establish to what extent fusion of the approaches is possible and beneficial. A second motivation is the need to advance emotion recognition systems to be able to deal with naturalistic behaviour in large volumes of unsegmented, non-prototypical and non-preselected. As you will see, these goals have been reachedwith the selection of this year's data and the challenge contributions. The call for participation and papers attracted registrations of 27 teams from all over the world, resulting in 7 submissions. The programme committee accepted 4 papers in addition to the baseline paper, which was reviewed independently. Three papers used fully audio-visual techniques and one paper used only the audio modality. Three papers addressed the depression recognition challenge, and one the affect recognition challenge. We hope that these proceedings will serve as a valuable reference for researchers and developers in the area of audio-visual emotion recognition and depression analysis. We are also thankful for the keynote speaker. This valuable and insightful talk can and will guide us to a better understanding of the state of the field, and future directions: Automated Analysis of Depressive Behaviour, Prof Jeff Cohn (who is currently at the University of Pittsburgh/ Carnegie Mellon University, USA). |
| ISBN | 9781450323956 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2013-10-21 |
| Access Restriction | Subscribed |
| Content Type | Text |
| Resource Type | Conference Proceedings |
