HEAT-MAP BASED EMOTION AND FACE RECOGNITION FROM THERMAL IMAGES

Nowadays, emotion recognition has become a feasible problem with implementation of Convolutional Neural Networks in Computer Vision domain. However, credibility of emotion recognition from daily images or videos is not enough. As people can easily mimic emotions one after another and fooling the trained models, a different approach should be taken into consideration. Thermal cameras would be a suitable way to develop more credible emotion recognition models. Heat-map of faces proved hinting emotions before, and it is not easy to fool the models trained from thermal heat-maps as it visualizes state of the body’s heat. In this research a method is adapted for training a model for recognizing emotions from thermal heat-mapped cameras with a fast detection algorithm -YOLOv3-. With this method the main aim is to detecting emotions from a given picture which taken from thermal cameras

Minutiae Based Thermal Human Face Recognition using Label Connected Component Algorithm

In this paper, a thermal infra red face recognition system for human identification and verification using blood perfusion data and back propagation feed forward neural network is proposed. The system consists of three steps. At the very first step face region is cropped from the colour 24-bit input images. Secondly face features are extracted from the croped region, which will be taken as the input of the back propagation feed forward neural network in the third step and classification and recognition is carried out. The proposed approaches are tested on a number of human thermal infra red face images created at our own laboratory. Experimental results reveal the higher degree performanceComment: 7 pages, Conference. arXiv admin note: substantial text overlap with arXiv:1309.1000, arXiv:1309.0999, arXiv:1309.100

Nose Heat: Exploring Stress-induced Nasal Thermal Variability through Mobile Thermal Imaging

Automatically monitoring and quantifying stress-induced thermal dynamic information in real-world settings is an extremely important but challenging problem. In this paper, we explore whether we can use mobile thermal imaging to measure the rich physiological cues of mental stress that can be deduced from a person's nose temperature. To answer this question we build i) a framework for monitoring nasal thermal variable patterns continuously and ii) a novel set of thermal variability metrics to capture a richness of the dynamic information. We evaluated our approach in a series of studies including laboratory-based psychosocial stress-induction tasks and real-world factory settings. We demonstrate our approach has the potential for assessing stress responses beyond controlled laboratory settings

Hyperspectral imaging for the remote sensing of blood oxygenation and emotions

This PhD project is a basic research and it concerns with how human’s physiological features, such as tissue oxygen saturation (StO2), can be captured from a stand-off distance and then to understand how this remotely acquired physiological feature can be deployed for biomedical and other applications. This work utilises Hyperspectral Imaging (HSI) within the diffuse optical scattering framework, to assess the StO2 in a contactless remote sensing manner. The assessment involves a detailed investigation about the wavelength dependence of diffuse optical scattering from the skin as well as body tissues, under various forms of optical absorption models. It is concluded that the threechromophore extended Beer Lambert Law model is better suited for assessing the palm and facial tissue oxygenations, especially when spectral data in the wavelengths region of [516-580]nm is used for the analysis. A first attempt of using the facial StO2 to detect and to classify people’s emotional state is initiated in this project. The objective of this work is to understand how strong emotions, such as distress that caused by mental or physical stimulations, can be detected using physiological feature such as StO2. Based on data collected from ~20 participants, it is found that the forehead StO2 is elevated upon the onset of strong emotions that triggered by mental stimulation. The StO2 pattern in the facial region upon strong emotions that are initiated by physical stimulations is quite complicated, and further work is needed for a better understanding of the interplays between bodily physique, individual’s health condition and blood transfusion control mechanism. Most of this work has already been published and future research to follow up when the author returns back to China is highlighted

Design of power device sizing and integration for solar-powered aircraft application

The power device constitutes the PV cell, rechargeable battery, and maximum power point tracker. Solar aircraft lack proper power device sizing to provide adequate energy to sustain low and high altitude and long endurance flight. This paper conducts the power device sizing and integration for solar-powered aircraft applications (Unmanned Aerial Vehicle). The solar radiation model, the aerodynamic model, the energy and mass balance model, and the adopted aircraft configuration were used to determine the power device sizing, integration, and application. The input variables were aircraft mass 3 kg, wingspan 3.2 m, chord 0.3 m, aspect ratio 11.25, solar radiation 825 W/m2 , lift coefficient 0.913, total drag coefficient 0.047, day time 12 hour, night time 12 hours, respectively. The input variables were incorporated into the MS Excel program to determine the output variables. The output variables are; the power required 10.92 W, the total electrical power 19.47 W, the total electrical energy 465.5 Wh, the daily solar energy 578.33 Wh, the solar cell area 0.62 m, the number of PV cell 32, and the number of the Rechargeable battery 74 respectively. The power device was developed with the PV cell Maxeon Gen III for high efficiency, the rechargeable battery sulfur-lithium battery for high energy density, and the Maximum power point tracker neural network algorithm for smart and efficient response. The PD sizing was validated with three existing designs. The validation results show that 20% reduction of the required number of PV cells and RB and a 30% increase in flight durations

Remote sensing of strong emotions using electro-optical imaging technique

©Cranfield UniversityThis thesis reports a summary of the PhD programme for the assessment of person‘s emotional anxiety using Electro-optical technology. The thesis focuses mainly on the understanding of fundamental properties of physiological responses to emotional anxiety and how they can be captured by using Electro-optical (EO) imaging methods such as hyperspectral imaging (HSI) and thermal imaging (TI) techniques. The thesis summarises three main areas of work that have been undertaken by the author in the programme: (a) Experimental set up including HSI system and data acquisition software design and implementation, (b) fundamental understanding of physiological responses to emotional anxiety from the EO perspective and (c) the development of a novel remote sensing technique for the assessment of emotions without the requirement of base line information. One of our main results is to provide evidence to prove that the mean temperature in the periorbital region remains the same within 0.2°C during emotional anxiety. Furthermore, we have shown that it is the high temperature pixels within the periorbital, which increases in numbers by a huge amount after 2 minutes of the onset of anxiety. We have also developed techniques to allow the assessment anxiety without the need of base line information. The method has been tested using a sample size of about 40 subjects, and achieved promising result. Technologies for the remote sensing of heart beat rate has been in great demand, this study also involves the development of heart beat detection using TI system. Moreover, we have also attempted for the first time to sense glucose concentration from the blood sample in-vivo using HSI technique remotely