Anomaly detection in facial skin temperature using variational autoencoder

Ayaka Masaki,Kosuke Oiwa,Akio Nozawa,Bikash Lamsal,Kent Nagumo

doi:10.1007/s10015-020-00634-2

Ayaka Masaki, Kosuke Oiwa + Show 3 more

Open Access

https://doi.org/10.1007/s10015-020-00634-2

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Abstract

Facial skin temperature is a physiological index that varies with skin blood flow controlled by autonomic nervous system activity. The facial skin temperature can be remotely measured using infrared thermography, and it has recently attracted attention as a remote biomarker. For example, studies have been reported to estimate human emotions, drowsiness, and mental stress on facial skin temperature. However, it is impossible to make a machine that can discriminate all infinite physiological and psychological states. Considering the practicality of skin temperature, a machine that can determine the normal state of facial skin temperature may be sufficient. In this study, we propose a completely new approach to incorporate the concept of anomaly detection into the analysis of physiological and psychological states by facial skin temperature. In this paper, the method for separating normal and anomaly facial thermal images using an anomaly detection model was investigated to evaluate the applicability of variational autoencoder (VAE) to facial thermal images.

Highlights

Facial skin temperature is a physiological index that varies with skin blood flow controlled by autonomic nervous system activity [1]
We propose the anomaly detection model for facial skin temperature using variational autoencoder (VAE) for the development of a machine that can judge the normal state of facial skin temperature
The method for separating normal and anomaly facial thermal images using an anomaly detection model was investigated to evaluate the applicability of VAE to facial thermal images

Summary

Introduction

Facial skin temperature is a physiological index that varies with skin blood flow controlled by autonomic nervous system activity [1]. The facial skin temperature can be remotely measured using infrared thermography, and it has recently attracted attention as a remote biomarker [2,3,4]. It has been known so far that there is some relationship between human physiological and psychological states and skin temperature at anatomical sites, but the appropriate size and position of region of interest (ROI) has not yet been clarified. We propose a completely new approach to incorporate the concept of anomaly detection [13] into the analysis of physiological and psychological states by facial skin temperature. The proposed anomaly detection algorithm separates the normal facial skin temperature

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