Human Health Monitoring Based on Computer Vision

Human Health Monitoring Based on Computer Vision has gained rapid scientific growth in recent years, with many research articles and complete systems based on set of features, extracted from face and gesture. Researchers from computer, as well as from medical science have granted significant attention, with goals ranging from patient analysis and monitoring to diagnostics, e.g., for Alzheimer’s disease, depression, healthcare, physiological measurement. Despite the progress, there are various open, unexplored, and unidentified challenges, making these techniques less robust in real application scenarios. Therefore, it is imperative to foster multidisciplinary efforts from computer vision, machine learning, and medical domain, etc. Towards this, we propose a special session, with focus on multidisciplinary efforts for Human Health Monitoring Based on Computer Vision. Therefore, the goal of this special session is to bring together researchers and practitioners working in the areas 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;
  • Visual attention and saliency;
  • Assistive living;
  • Privacy preserving systems;
  • Quality of life technologies.


Dr. François Brémond, INRIA Méditerranée Sophia Antipolis
Prof. Xilin Chen, University of Chinese Academy of Sciences, Institute of Computing Technology
A\Prof. Hu Han, University of Chinese Academy of Sciences, Institute of Computing Technology
Dr. Abhijit Das, Inria Méditerranée Sophia Antipolis
Dr. Antitza Dantcheva, INRIA Méditerranée Sophia Antipolis


    • Full Paper Submission: January 6, 2019 – midnight PST
    • Camera Ready Deadline for Accepted papers: March 13, 2019


Both long and short papers are accepted for submission to the Special Session, and all submissions should follow the standard IEEE FG2019 format. The submissions will be peer-reviewed following the same review process (double blind) as that of the FG2019 main conference, except that there will be NO rebuttal stage. Papers are required to be submitted to the CMT under this special session name. The CMT system will be open for new submissions before the deadline.

ANONYMISATION POLICY : Double blind reviews are used. Authors should remove author and institutional identi-ties from the title and header areas of the paper. There should also be no acknowledg-ments. Authors can leave citations to their previous work unanonymized so that review-ers can ensure that all previous research has been taken into account. However, they should cite their own work in the third person (e.g., “[22] found that…”).