Anomaly detection in facial skin temperature using variational autoencoder
| Autor: | Akio Nozawa, Ayaka Masaki, Kent Nagumo, Kosuke Oiwa, Bikash Lamsal |
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| Rok vydání: | 2020 |
| Předmět: |
integumentary system
Computer science business.industry Skin blood flow 05 social sciences Pattern recognition Normal state Autoencoder 050105 experimental psychology General Biochemistry Genetics and Molecular Biology Facial skin 03 medical and health sciences 0302 clinical medicine Artificial Intelligence Mental stress Thermography 0501 psychology and cognitive sciences Anomaly detection Artificial intelligence Anomaly (physics) business 030217 neurology & neurosurgery |
| Zdroj: | Artificial Life and Robotics. 26:122-128 |
| ISSN: | 1614-7456 1433-5298 |
| DOI: | 10.1007/s10015-020-00634-2 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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