Call for Papers

Click here to download the call for paper as pdf

The 2nd International Workshop on Computer Vision for Physiological Measurement (CVPM) will be held in conjunction with the Int'l Conference on Computer Vision (ICCV 2019) in Seoul, South Korea (October 27th - November 2nd 2019). Accepted papers will be published in IEEExplore.

CVPM 2019 aims to explore the devices, algorithms and applications of image and video-based physiological measurement.

We invite high-quality submission of original research addressing one or more of the following topics:

  • Novel/improved methods/algorithms for extracting physiological signals/variables from videos, including pulse rate, pulse rate variability, respiration rate, blood oxygen, pulse transit time, blood pressure, atrial fibrillation, arterial stiffness, skin hydration and core body temperature.
  • Novel/improved methods/algorithms for camera-based physiological monitoring systems, such as CNN-based face/skin detection, motion tracking, video segmentation, quality metric learning, physiological pattern recognition and algorithmic optimization.
  • Novel/improved apparatuses/imaging devices for sensing physiological signals from the human face and body, including multi-spectral, hyper-spectral, time sequential, time-of-flight, stereo vision, long- distance, portable, and low-cost cameras that are sensitive at visible, near-/far- infrared, or thermal wavelengths.
  • Applications for video health monitoring in domains such as Intensive Care Units (ICU), Neonatal Intensive Care Units (NICU), general medical wards, triage in emergency department, elderly care at home. Applications such as sleep monitoring, bed exit detection, fall detection, fitness cardio-training and driver state monitoring.
  • Camera-based physiological measurement for detecting affective, emotional, or cognitive states.
  • Camera-based physiological measurement to assist video surveillance in-the-wild.
  • Camera-based physiological measurement to assist human computer interaction, entertainment, gaming, and marketing.
  • Living skin detection and human liveness detection.
  • Face anti-spoofing and biometric recognition.
  • New public benchmarks and datasets for camera-based physiological measurement.
  • Using video semantics to interpret patient/neonatal actigraphy (behavior recognition and analysis).
  • Vision based clinical/hospital environment monitoring.
  • Using AI to interpret physiological measurement in ICU and NICU.
  • AI-assisted big data analysis for healthcare applications.