Call for Paper

Link to the online proceedings of the workshop on Springer:

http://www.springer.com/gp/book/9783319566863

 

The accepted papers of FACE AND FACIAL EXPRESSION RECOGNITION (FFER) will be published jointly with the accepted papers of another ICPR workshop VIDEO ANALYTICS FOR AUDIENCE MEASUREMENT (VAAM 2016) under a Springer’s post-proceedings: Video Analytics for Face, Facial Expression Recognition, and Audience Measurement

The accepted papers of VAAM can be seen at the following link: http://vaam.isasi.cnr.it/styled-3/index.html

The accepted papers of FFER can be seen here: http://www.vap.aau.dk/ffer16/?page_id=15

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Professor Matti Pietikäinen from University of Oulu in Finland will give the keynote speech.

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The 2nd workshop on face and facial expression recognition (FFER 2016) from real world videos in conjunction with ICPR 2016, Cancun, Mexico, Dec. 4th 2016.

The face plays a key role in many real-world applications such as security systems, human computer interaction, remote monitoring of patients, video annotation, and gaming. Having detected the face, pattern recognition techniques and machine learning algorithms are applied to facial images, for example, to find the identity of a subject or analyze her/his emotional status. Though face and facial expression recognition in still images and in ideal imaging conditions have been around for many years, they have been less explored in video sequences in uncontrolled imagining conditions. Developing face and facial expression recognition algorithms for real-world scenarios, for instance, for remote patient monitoring or for identification in surveillance videos are still challenging tasks. The purpose of this workshop is to bring together researchers who are working on developing face and facial expression recognition systems that involve non-ideal conditions, like those that might be present in a video. We welcome research papers focusing on the following (and similar) topics:

  • Video face recognition
  • Video facial expression recognition
  • Face and facial expression recognition from facial dynamics
  • Multi-face clustering from video
  • Deep learning based facial analysis systems
  • 3D face modeling from video
  • Multimodal face and facial expression recognition
  • Applications of video face recognition
  • Applications of video facial expression recognition

 

Lecture Notes in Computer Science

The post-proceedings of FFER 2016 will be published by Springer’s LNCS series.