Dear colleagues,

 

We are organizing a special session on “Computer Vision for Automatic Human Health Monitoring” in conjunction with 15th IEEE Conference on

Automatic Face and Gesture Recognition to be held between 18th-22th May 2020 in Buenos Aires, Argentina. Kindly find the related call for papers below.   

Papers submission deadline: 10th January 2019 – midnight PST (firm deadline no further extension)

Paper notification deadline: 10th February 2020

Final camera-ready papers: 28 February 2020

Submission instructions can be found at https://fg2020.org/instructions-of-paper-submission-for-review/. 

For submission log into https://cmt3.research.microsoft.com/FG2020/Submission/Index, proceed to “create new submission”. Select “special session track and subject area” as “Special session: Computer Vision for Automatic Human Health Monitoring”.

Please feel free to contact us for any further details. Kindly disseminate this email to others who might be interested.

We look forward to your contributions.

Antitza Dantcheva (INRIA, France)  

Abhijit Das (USC, USA)

François Brémond  (INRIA, France)

Xilin Chen  (CAS, China)

Hu Han (CAS, China)

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Automatic Human Health Monitoring Based on Computer Vision has gained rapid scientific attention in the decade, fueled by a large number of research articles and commercial systems based on set of features, extracted from face and gesture. Consequently, researchers from computer vision, as well as from medical science community have granted significant attention, with goals ranging from patient analysis and monitoring to diagnostics.  The goal of this special session is to bring together researchers and practitioners working in this area of computer vision and medical science, and to address a wide range of theoretical and practical issues related to real-life healthcare systems.

Topics of interest include, but are not limited to:

 Health monitoring based on face analysis,

 Health monitoring based on gesture analysis,

 Health monitoring based corporeal-based visual features,

 Depression analysis based on visual features,

 Face analytics for human behavior understanding,

 Anxiety diagnosis based on face and gesture,

 Physiological measurement employing face analytics,

 Databases on health monitoring, e.g., depression analysis,

 Augmentative and alternative communication,

 Human-robot interaction,

 Home healthcare,

 Technology for cognition,

 Automatic emotional hearing and understanding,

 Visual attention and visual saliency,

 Assistive living,

 Privacy preserving systems,

 Quality of life technologies,

 Mobile and wearable systems,

 Applications for the visually impaired,

 Sign language recognition and applications for hearing impaired,

 Applications for the ageing society,

 Personalized monitoring,

 Egocentric and first-person vision,

 Applications to improve health and wellbeing of children and elderly.