Adaptive Eulerian Video Processing of Thermal Video: An Experimental Analysis

The use of spatiotemporal video processing to extract biosignals is an emerging technique. This paper aims to build upon current work through robust experimentation and analysis. A blood flow simulation model was captured by thermal and optical cameras, while hot water was pumped through the system. Additionally, five subjects were recruited to perform two experimental trials: a facial perfusion trial and an arm blood occlusion trial, for which subjects sat quietly, while video data were captured using thermal and optical cameras. Each video was subjected to region of interest selection and adaptive Eulerian video magnification (EVM); the iterative application of EVM, first with a wide temporal bandpass filter and low amplification factor and again with a narrower, targeted temporal bandpass filter and higher amplification factor. The results from the simulation experiments indicated that thermal video in conjunction with adaptive EVM processing can reveal variations in temperature indicative of pulse rate in a controlled system of known variables. This process helped to better characterize Eulerian signal enhancement versus Eulerian noise enhancement. The results from the facial perfusion experiments suggest that the adaptive EVM processing of thermal video results in signals representative of facial perfusion rate. The results from the blood occlusion experiments revealed an occlusion temperature pattern, but not a perfusion rate. This paper therefore further demonstrated the potential of thermal video in conjunction with adaptive EVM methods to extract a signal representative of facial perfusion rate, and illustrated the need for more research on thermal video and adaptive EVM.