[Face-research-list] Call for abstracts: special session on human health monitoring based on computer vision, IEEE International Conference on Automatic Face and Gesture Recognition (FG’19), Lille, France, May 14-18, 2019.

ABHIJIT DAS abhijitdas2048 at gmail.com
Fri Sep 21 10:51:45 BST 2018

Dear colleagues,

We are inviting abstract submissions for a special session on “Human Health
Monitoring Based on Computer Vision”, as part of the 14th IEEE
International Conference on Automatic Face and Gesture Recognition (FG’19,
http://fg2019.org/), Lille, France, May 14-18, 2019. Details on the special
session follow below.

Title, abstract, list of authors, as well as the name of the corresponding
author, should be emailed directly to Abhijit Das (abhijitdas2048 at gmail.com).
We hope to receive abstracts before Thursday, September 27th.

Feel free to contact Abhijit Das if you have any further questions.

Kindly circulate this email to others who might be interested.

We look forward to your contributions!

François Brémond  (INRIA, France)

Antitza Dantcheva (INRIA, France)

Abhijit Das (INRIA, France)

Xilin Chen  (CAS, China)

Hu Han (CAS, China)

*Call for abstract for FG 2018 special session *


*Human Health Monitoring Based on Computer Vision*


Human Health Monitoring Based on Computer Vision has gained rapid
scientific growth in the last years, with many research articles and
complete systems based on a set of features, extracted from face and
gesture. Researchers from the computer, as well as from medical science
have granted significant attention, with goals ranging from patient
analysis and monitoring to diagnostics. (e.g., for dementia, depression,
healthcare, physiological measurement [5, 6]).

   Despite the progress, there are various open, unexplored, and
unidentified challenges.  Such as the robustness of these techniques in the
real-world scenario, collecting large dataset for research, heterogeneity
of the acquiring environment and the artefacts. Moreover, healthcare
represents an area of broad economic (e.g.,
social, and scientific impact. Therefore, it is imperative to foster
efforts coming from computer vision, machine learning, and the medical
domain, as well as multidisciplinary efforts. Towards this, we propose a
special session, with a focus on multidisciplinary efforts. We aim to
document recent advancements in automated healthcare, as well as enable and
discuss progress.. Therefore, 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 behaviour 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 the health and wellbeing of children and
the elderly, etc.

In addition, we plan to organise a special issue in a journal with the
extended version of accepted special session papers.
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