from April 2014. His research interest includes face detection, image processing, augmented reality, virtual reality, software design, robotics and algorithm design.

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.

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This paper is associated with an autotuning stochastic resonance (SR) approach for image enhancement on illumination variant images. This new process is being developed based on our previous works related to image enhancement by using SR through the manual tuning process. The process was performed by adding the random noise and threshold 0 in an image. The process works properly in the dark and very low contrast images as well as bright images based and mixed illumination variant images. This system works on the images with the mixture of darkness and brightness. We also present the idea of autotuning of the iteration with random noise and threshold value 0 by using the process related to the histogram calculation or mean and median. We performed various experiments on various types of images including human faces under different conditions and confirmed the effectiveness of our image enhancement technique. K E Y W O R D Sface detection, image enhancement, parameter autotuning, severe photographing condition, stochastic resonance Electron Comm Jpn. 2019;102:35-46.