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Call for abstract for FG 2018 special session 

on  

Human Health Monitoring Based on Computer Vision

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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., https://www.prnewswire.com/news-releases/healthcare-automation-market-to-reach-us5898-billion-by-2025-smarter-technologies-up-the-game-for-automated-solutions-in-healthcare-industry-622761234.html), 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.