AVEC 2013

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Call for papers:

Organisers

Björn Schuller

TUM, Germany

schuller@tum.de

 

Michel Valstar        

University of Nottingham, UK

michel.valstar@nottingham.ac.uk

 

Roddy Cowie        

Queen’s University Belfast, UK

r.cowie@qub.ac.uk

 

Maja Pantic        

Imperial College London, UK

m.pantic@imperial.ac.uk

 

Jarek Krajewski        

University of Wuppertal, DE

krajewski@uni-wuppertal.de

Scope

The Audio/Visual Emotion Challenge and Workshop (AVEC 2013) will be the third competition event aimed at comparison of multimedia processing and machine learning methods for automatic audio, visual and audio-visual emotion analysis, with all participants competing under strictly the same conditions.

The AVEC 2013 edition features besides emotion recognition the serious and important automatic estimation of levels of depression. Adding objective measures to what is otherwise an entirely subjective process of diagnosing and monitoring depression promises to be an invaluable support to the mental health profession besides the usage in media retrieval systems.

The goal of the Challenge 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 behavior in large volumes of un-segmented, non-prototypical and non-preselected data as this is exactly the type of data that both multimedia retrieval and human-machine/human-robot communication interfaces have to face in the real world.

We are calling for teams to participate in two Sub-Challenges: fully-continuous emotion detection from audio, from video, or from audio-visual information, and estimation of a depression severity indicator. As benchmarking database the audio-visual depression corpus database of task-specific human-computer interactions will be used. Emotion will have to be recognized in terms of continuous time, continuous valued dimensional affect in two dimensions: arousal and valence. Depression will have to be estimated in terms of a widely accepted clinical self-report questionnaire, the Beck Depression Inventory II.

Besides participation in the Challenge we are calling for papers addressing the overall topics of this workshop, in particular works that address the differences between audio and video processing of emotive data, and the issues concerning combined audio-visual emotion recognition.

Program Committee

Elisabeth André, Universität Augsburg, Germany

Anton Batliner, Universität Erlangen-Nuremberg, Germany

Felix Burkhardt, Deutsche Telekom, Germany

Rama Chellappa, University of Maryland, USA

Mohamed Chetouani, Institut des Systèmes Intelligents et de Robotique (ISIR), Fance

Jeff Cohn, University of Pittsburgh/Carnegie Mellon University, USA

Laurence Devillers, Laboratoire d’Informatique pour la Mécanique et les Sciences de l’Ingénieur (LIMSI), France

Julien Epps, University of New South Wales, Australia

Roland Göcke, Australian National University, Australia

Hatice Gunes, Queen Mary University London, UK

Aleix Martinez, Ohio State University, USA

Marc Méhu, University of Geneva, Switzerland

Louis-Philippe Morency, University of Southern California, USA

Marcello Mortillaro, University of Geneva, Switzerland

Stefan Scherer, University of Southern California, USA

Stefan  Steidl, Uinversität Erlangen-Nuremberg, Germany

Jianhua Tao, Chinese Academy of Sciences, China

Fernando de la Torre, Carnegie Mellon University, USA

Stefanos Zafeiriou, Imperial College London, UK


Important Dates

Paper submission July, 2013

Notification of acceptance July/August, 2013

Camera ready paper August, 2013

Workshop Monday 21 October, 2013

Topics include, but are not limited to: 

Participation in the Challenge
Audio-Visual Depression and Emotion Recognition

  • Audio-based Depression and Emotion Recognition
  • Linguistics-based Depression and Emotion Recognition
  • Video-based Depression and Emotion Recognition
  • Social Signals in Depression and Emotion Recognition
  • Multi-task learning of Multiple Dimensions
  • Agglomeration of Learning Data
  • Weakly Supervised Learning
  • Context in Audio/Visual Emotion Recognition
  • Multiple Rater ambiguity

Application

  • Multimedia Coding and Retrieval
  • Real-time Issues

Submission Policy

In submitting a manuscript to this workshop, the authors acknowledge that no paper substantially similar in content has been submitted to another conference or workshop. Accepted workshop papers will be included in the proceedings of ACM Multimedia 2013. AVEC 2013 reviewing is double blind. Reviewing will be by members of the program committee. Each paper will receive at least three reviews. Acceptance will be based on relevance to the workshop, novelty, and technical quality.