Mental Stress Detection Based on Stereo Vision Fusion Measurement

Mohd Norzali Haji Mohd

Abstract


This paper aims to present a novel methodology for real time monitoring of Internal Emotion State (Mental Stress). The method does not require any contact as contact measurement tend to effect emotions and burden physiologically. We have found out that user stress is correlated with the increased blood flow in three facial areas of sympathetic importance which is periorbital, supraorbital and maxillary. This increased blood flow dissipates convective heat which can be monitored through thermal imaging. In the stress experiment conducted, blood vessel is also detected via thermal imaging for several subjects in real time. Thermal infrared and visible cameras are being used in the stimulus experiment. Sample of several faces are also taken in real time in our experimental setup to measure the effectiveness of our method. Almost 98% of correct measurement of ROI and temperature was detected. The results of temperature before and after stress stimulus experiment are also compared and show promising results.

In this paper also, a new method for detecting facial feature in both thermal and visual is presented by applying Nostril Mask, which allows one to find facial feature namely nose area in thermal and visual. Graph Cut algorithm is applied to remove unwanted ROI and correctly detect precise temperature values. Extraction of thermal-visual facial feature images is done by using Scale Invariant Feature Transform (SIFT) Feature detector and extractor to verify the method of using nostril mask. Based on the experiment conducted, it shows 88.6% of correct matching. The detection result of  eyes blinking also show promising results.

An Accurate and efficient thermal-infrared camera calibration is also important for advancing computer vision research approach for geometrically calibrating individual and multiple cameras in both thermal and visible modalities. We also propose new printed Fever Cold Plaster (FCP) chessboard using a popular existing approach which is comparatively accurate and simple to execute. Based on the experiment conducted by comparing the degradation of image quality with the current approach, our proposed chessboard can be more clearly located than those on the applied standard chessboard by 39%.


Keywords


Camera calibration, Face and gesture recognition, Edge and feature detection, Image processing software

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