Abstract
Our main aim is to propose a vision-based measurement as an alternative to physiological measurement for recognizing mental stress. The development of this emotion recognition system involved three stages: experimental setup for vision and physiological sensing, facial feature extraction in visual-thermal domain, mental stress stimulus experiment and data analysis and classification based on Support Vector Machine. In this research, 3 vision-based measurement and 2 physiological measurement were implemented in the system. Vision based measurement in facial vision domain consists of eyes blinking and in facial thermal domain consists 3 ROI’s temperature value and blood vessel volume at Supraorbital area. Two physiological measurement were done to measure the ground truth value which is heart rate and salivary amylase level. We also propose a new calibration chessboard attach with fever plaster to locate calibration point in stereo view. A new method of integration of two different sensors for detecting facial feature in both thermal and visual is also presented by applying nostril mask, which allows one to find facial feature namely nose area in thermal and visual domain. Extraction of thermal-visual feature images was done by using SIFT feature detector and extractor to verify the method of using nostril mask. Based on the experiment conducted, 88.6 % of correct matching was detected. In the eyes blinking experiment, almost 98 % match was detected successfully for without glasses and 89 % with glasses. Graph cut algorithm was applied to remove unwanted ROI. The recognition rate of 3 ROI’s was about 90 %–96 %. We also presented new method of automatic detection of blood vessel volume at Supraorbital monitored by LWIR camera. The recognition rate of correctly detected pixel was about 93 %. An experiment to measure mental stress by using the proposed system based on Support Vector Machine classification had been proposed and conducted and showed promising results.
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Acknowledgment
This work was partially funded by MEXT/JSPS Kakenhi grant number: 50325768 and University Tun Hussein Onn Malaysia (UTHM). We would like to give special thanks to the laboratory members for their invaluable inputs and assistance.
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Mohd, M.N.H., Kashima, M., Sato, K., Watanabe, M. (2015). A Non-invasive Facial Visual-Infrared Stereo Vision Based Measurement as an Alternative for Physiological Measurement. In: Jawahar, C., Shan, S. (eds) Computer Vision - ACCV 2014 Workshops. ACCV 2014. Lecture Notes in Computer Science(), vol 9009. Springer, Cham. https://doi.org/10.1007/978-3-319-16631-5_50
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