Diferencia entre revisiones de «KES2008-3DFACE»
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| (No se muestran 6 ediciones intermedias de 2 usuarios) | |||
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= | ==Special session: Intelligent 3D approaches for visual facial expression and emotion dynamics recognition in a real time context== | ||
=== Chairs=== | |||
Andoni Beristain | |||
==Description== | Manuel Graña | ||
Computational Intelligence Group, UPV/EHU | |||
===Contact email=== | |||
manuel.grana@ehu.es | |||
===Description=== | |||
Emotion recognition based on the analysis of facial expressions is a growing research area. Systems are becoming more and more complex, and most of the research is turning into a 3D approach, using generic 3D face or head models. Most recent work’s trend takes into account the dynamics of facial expressions when trying to recognize emotions using techniques like Hidden Markov Models. For most of the practical applications a real time response is required. We are interested in novel procedures for facial feature tracking, techniques for 3D model adaptation to subjects’ faces, 3D tracking of facial features and facial expression dynamics’ modelling and classification. We want to focus on the use of ordinary colour cameras. Stereo vision based procedures are welcome. | Emotion recognition based on the analysis of facial expressions is a growing research area. Systems are becoming more and more complex, and most of the research is turning into a 3D approach, using generic 3D face or head models. Most recent work’s trend takes into account the dynamics of facial expressions when trying to recognize emotions using techniques like Hidden Markov Models. For most of the practical applications a real time response is required. We are interested in novel procedures for facial feature tracking, techniques for 3D model adaptation to subjects’ faces, 3D tracking of facial features and facial expression dynamics’ modelling and classification. We want to focus on the use of ordinary colour cameras. Stereo vision based procedures are welcome. | ||
== | ===Important dates=== | ||
March 15 Soft deadline for paper submission, papers arriving after this date will be subjected to reviewer availability. | |||
April 15 Acceptance notification | |||
April 25 Final camera ready papers uploaded | |||
===Topics of interest=== | |||
* Facial feature tracking using 3D generic facial models. | |||
* 3D adaptable face meshes using FACS of FAPS units and taking into account anatomic restrictions like muscles and proportions. | |||
* Head and facial feature motion classification into facial expressions, emotions and mental states. | |||
* Practical applications developed following the above criteria. | |||
Revisión actual - 00:36 1 feb 2008
Special session: Intelligent 3D approaches for visual facial expression and emotion dynamics recognition in a real time context
Chairs
Andoni Beristain
Manuel Graña
Computational Intelligence Group, UPV/EHU
Contact email
manuel.grana@ehu.es
Description
Emotion recognition based on the analysis of facial expressions is a growing research area. Systems are becoming more and more complex, and most of the research is turning into a 3D approach, using generic 3D face or head models. Most recent work’s trend takes into account the dynamics of facial expressions when trying to recognize emotions using techniques like Hidden Markov Models. For most of the practical applications a real time response is required. We are interested in novel procedures for facial feature tracking, techniques for 3D model adaptation to subjects’ faces, 3D tracking of facial features and facial expression dynamics’ modelling and classification. We want to focus on the use of ordinary colour cameras. Stereo vision based procedures are welcome.
Important dates
March 15 Soft deadline for paper submission, papers arriving after this date will be subjected to reviewer availability.
April 15 Acceptance notification
April 25 Final camera ready papers uploaded
Topics of interest
- Facial feature tracking using 3D generic facial models.
- 3D adaptable face meshes using FACS of FAPS units and taking into account anatomic restrictions like muscles and proportions.
- Head and facial feature motion classification into facial expressions, emotions and mental states.
- Practical applications developed following the above criteria.
