Multimodal data acquisition at SARS-CoV-2 drive through screening centers: Setup description and experiences in Saarland, Germany.

SARS-CoV-2 drive through screening centers (DTSC) have been implemented worldwide as a fast and secure way of mass screening. We use DTSCs as a platform for the acquisition of multimodal datasets that are needed for the development of remote screening methods. Our acquisition setup consists of an array of thermal, infrared and RGB cameras as well as microphones and we apply methods from computer vision and computer audition for the contactless estimation of physiological parameters. We have recorded a multimodal dataset of DTSC participants in Germany for the development of remote screening methods and symptom identification. Acquisition in the early stages of a pandemic and in regions with high infection rates can facilitate and speed up the identification of infection specific symptoms and large-scale data acquisition at DTSC is possible without disturbing the flow of operation.

Towards Contactless Estimation of Electrodermal Activity Correlates.

This paper presents a proof-of-concept for contactless and nonintrusive estimation of electrodermal activity (EDA) correlates using a camera. RGB video of the palm under three different lighting conditions showed that for a suitably chosen illumination strategy the data from the camera is sufficient to estimate EDA correlates which agree with the measurements done using laboratory grade physiological sensors. The effects we see in the recorded video can be attributed to sweat gland activity, which inturn is known to be correlated with EDA. These effects are so pronounced that simple pixel statistics can be used to quantify them. Such a method benefits from advances in computer vision and graphics research and has the potential to be used in affective computing and psychophysiology research where contact based sensors may not be suitable.

Lagrangian Motion Magnification revisited: Continuous, Magnitude Driven Motion Scaling for Psychophysiological Experiments.

Video motion magnification forms a relatively novel family of visualization techniques, that aim to magnify imperceivably small motions in videos. The most prominent techniques are based on Eulerian video processing and local phase shifting, which modify pixel time courses, rather than relying on explicit motion estimation.In this work, we show that under ideal conditions in the context of psychophysiological experiments, a Lagrangian motion magnification approach based on dense optical flow estimation, can be superior to Eulerian motion magnification strategies. We present a novel, continuous and motion magnitude driven forward warping scheme of small motions, which implements motion compensation and magnification into a single motion estimation step. Our approach does not rely on temporal filtering and works in the presence of large motion. It does not require the explicit identification of fast moving objects and more generally no segmentation and or matting in the image domain is necessary. We apply our method to the visualization of blinking related modulations in micro-saccadic eye movements ((i.a.. iridodonesis), pupil dilation (hippus) and micro-expression analysis.