scholarly journals Non-Invasive Forehead Segmentation in Thermographic Imaging

Sensors ◽  
2019 ◽  
Vol 19 (19) ◽  
pp. 4096 ◽  
Author(s):  
Francisco J. Rodriguez-Lozano ◽  
Fernando León-García ◽  
M. Ruiz de Adana ◽  
Jose M. Palomares ◽  
J. Olivares
Keyword(s):  
User Interaction ◽  
Lie Detection ◽  
Detection Systems ◽  
Average Temperature ◽  
Non Invasive ◽  
Face Images ◽  
The Face ◽  
Highly Correlated ◽  
Thermal Face ◽  
Computational Resources

The temperature of the forehead is known to be highly correlated with the internal body temperature. This area is widely used in thermal comfort systems, lie-detection systems, etc. However, there is a lack of tools to achieve the segmentation of the forehead using thermographic images and non-intrusive methods. In fact, this is usually segmented manually. This work proposes a simple and novel method to segment the forehead region and to extract the average temperature from this area solving this lack of non-user interaction tools. Our method is invariant to the position of the face, and other different morphologies even with the presence of external objects. The results provide an accuracy of 90% compared to the manual segmentation using the coefficient of Jaccard as a metric of similitude. Moreover, due to the simplicity of the proposed method, it can work with real-time constraints at 83 frames per second in embedded systems with low computational resources. Finally, a new dataset of thermal face images is presented, which includes some features which are difficult to find in other sets, such as glasses, beards, moustaches, breathing masks, and different neck rotations and flexions.

scholarly journals Face Recognition and Drunk Classification Using Infrared Face Images

2018 ◽  
Vol 2018 ◽  
pp. 1-8 ◽  
Author(s):  
Gabriel Hermosilla ◽  
José Luis Verdugo ◽  
Gonzalo Farias ◽  
Esteban Vera ◽  
Francisco Pizarro ◽  
...  
Keyword(s):  
Face Recognition ◽  
Promising Result ◽  
Gaussian Mixture ◽  
Local Descriptor ◽  
Linear Discriminant ◽  
Face Images ◽  
The Face ◽  
Robust Face Recognition ◽  
Thermal Face ◽  
Two Stages

The aim of this study is to propose a system that is capable of recognising the identity of a person, indicating whether the person is drunk using only information extracted from thermal face images. The proposed system is divided into two stages, face recognition and classification. In the face recognition stage, test images are recognised using robust face recognition algorithms: Weber local descriptor (WLD) and local binary pattern (LBP). The classification stage uses Fisher linear discriminant to reduce the dimensionality of the features, and those features are classified using a classifier based on a Gaussian mixture model, creating a classification space for each person, extending the state-of-the-art concept of a “DrunkSpace Classifier.” The system was validated using a new drunk person database, which was specially designed for this work. The main results show that the performance of the face recognition stage was 100% with both algorithms, while the drunk identification saw a performance of 86.96%, which is a very promising result considering 46 individuals for our database in comparison with others that can be found in the literature.

scholarly journals Thermal Face Verification through Identification

Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 3301
Author(s):  
Artur Grudzień ◽  
Marcin Kowalski ◽  
Norbert Pałka
Keyword(s):  
Face Verification ◽  
Image Method ◽  
Double Image ◽  
New Approach ◽  
Long Wavelength ◽  
Face Images ◽  
The Face ◽  
Thermal Face ◽  
Spectral Ranges ◽  
Long Wavelength Infrared

This paper reports on a new approach to face verification in long-wavelength infrared radiation. Two face images were combined into one double image, which was then used as an input for a classification based on neural networks. For testing, we exploited two external and one homemade thermal face databases acquired in various variants. The method is reported to achieve a true acceptance rate of about 83%. We proved that the proposed method outperforms other studied baseline methods by about 20 percentage points. We also analyzed the issue of extending the performance of algorithms. We believe that the proposed double image method can also be applied to other spectral ranges and modalities different than the face.

A Single-Center Trial to Evaluate the Efficacy and Tolerability of Four Microneedling Treatments on Fine Lines and Wrinkles of Facial and Neck Skin in Subjects With Fitzpatrick Skin Types I-IV: An Objective Assessment Using Non-Invasive Devices and 0.33mm Microbiopsies

2021 ◽  
Author(s):  
Christine E Wamsley ◽  
Mikaela Kislevitz ◽  
Jennifer Barillas ◽  
Deniz Basci ◽  
Vishal Kandagatla ◽  
...  
Keyword(s):  
Gene Expression ◽  
Objective Assessment ◽  
Standard Of Care ◽  
Transepidermal Water Loss ◽  
Post Treatment ◽  
Non Invasive ◽  
Muscle Formation ◽  
The Face ◽  
High Resolution Ultrasonography ◽  
Elastin Gene

Abstract Background While ablative techniques have been standard of care for the treatment of fine lines and wrinkles, microneedling is a minimally invasive alternative. Objectives The purpose of this study was to assess the efficacy of microneedling on facial and neck fine lines and wrinkles. Methods 35 subjects between 44 and 65 years old with Fitzpatrick skin types I-IV received four monthly microneedling treatments over the face and neck. Subjects returned one and three months post-treatment. At every visit, high-resolution ultrasonography, optical coherence tomography, transepidermal water loss and BTC-2000 were performed. 0.33mm microbiopsies were collected pre-treatment, before the fourth treatment and three months post-treatment. Results 32 subjects (93.75% female, 6.25% male) completed all seven visits. Facial dermal and epidermal density increased 101.86% and 19.28%, respectively from baseline at three months post-treatment. Facial elasticity increased 28.2% from baseline three months post-treatment. Facial attenuation coefficient increased 15.65% and 17.33% one and three months post-treatment. At study completion, blood flow 300µm deep decreased 25.8% in the face and 42.3% in the neck. Relative collagen type III and elastin gene expression was statistically higher three months post-treatment. However, total elastin protein levels unchanged compared to baseline. 58% of biopsies extracted three months post-treatment showed dermal muscle formation, compared to baseline 15.3%. Conclusions The results illustrate the effects of microneedling treatments. Non-invasive measurements and biopsy data showed changes in skin architecture and collagen/elastin gene expression suggesting skin rejuvenation, with new extracellular matrix production and muscle formation.

scholarly journals Design of Thermal Insulation Materials with Different Geometries of Channels

Polymers ◽  
2021 ◽  
Vol 13 (13) ◽  
pp. 2217
Author(s):  
Daniela Șova ◽  
Mariana Domnica Stanciu ◽  
Sergiu Valeriu Georgescu
Keyword(s):  
Thermal Conductivity ◽  
Porous Structure ◽  
Base Material ◽  
Cost Effective ◽  
Heat Radiation ◽  
Average Temperature ◽  
Temperature Regimes ◽  
The Face ◽  
Inclined Channels ◽  
Air Channels

Investigating the large number of various materials now available, some materials scientists promoted a method of combining existing materials with geometric features. By studying natural materials, the performance of simple constituent materials is improved by manipulating their internal geometry; as such, any base material can be used by performing millimeter-scale air channels. The porous structure obtained utilizes the low thermal conductivity of the gas in the pores. At the same time, heat radiation and gas convection is hindered by the solid structure. The solution that was proposed in this research for obtaining a material with porous structure consisted in perforating extruded polystyrene (XPS) panels, as base material. Perforation was performed horizontally and at an angle of 45 degrees related to the face panel. The method is simple and cost-effective. Perforated and simple XPS panels were subjected to three different temperature regimes in order to measure the thermal conductivity. There was an increase in thermal conductivity with the increase in average temperature in all studied cases. The presence of air channels reduced the thermal conductivity of the perforated panels. The reduction was more significant at the panels with inclined channels. The differences between the thermal conductivity of simple XPS and perforated XPS panels are small, but the latter can be improved by increasing the number of channels and the air channels’ diameter. Additionally, the higher the thermal conductivity of the base material, the more significant is the presence of the channels, reducing the effective thermal conductivity. A base material with low emissivity may also reduce the thermal conductivity.

Face recognition in an intelligent door lock with ResNet model based on deep learning

2021 ◽  
pp. 1-11
Author(s):  
Suphawimon Phawinee ◽  
Jing-Fang Cai ◽  
Zhe-Yu Guo ◽  
Hao-Ze Zheng ◽  
Guan-Chen Chen
Keyword(s):  
Face Recognition ◽  
Detection System ◽  
Low Cost ◽  
Ease Of Use ◽  
Raspberry Pi ◽  
Training Methods ◽  
Graphics Recognition ◽  
Face Images ◽  
The Face ◽  
Door Lock

Internet of Things is considerably increasing the levels of convenience at homes. The smart door lock is an entry product for smart homes. This work used Raspberry Pi, because of its low cost, as the main control board to apply face recognition technology to a door lock. The installation of the control sensing module with the GPIO expansion function of Raspberry Pi also improved the antitheft mechanism of the door lock. For ease of use, a mobile application (hereafter, app) was developed for users to upload their face images for processing. The app sends the images to Firebase and then the program downloads the images and captures the face as a training set. The face detection system was designed on the basis of machine learning and equipped with a Haar built-in OpenCV graphics recognition program. The system used four training methods: convolutional neural network, VGG-16, VGG-19, and ResNet50. After the training process, the program could recognize the user’s face to open the door lock. A prototype was constructed that could control the door lock and the antitheft system and stream real-time images from the camera to the app.

scholarly journals Enhanced use of gaze cue in a face-following task after brief trial experience in individuals with autism spectrum disorder

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Takao Fukui ◽  
Mrinmoy Chakrabarty ◽  
Misako Sano ◽  
Ari Tanaka ◽  
Mayuko Suzuki ◽  
...  
Keyword(s):  
Autism Spectrum ◽  
Face Image ◽  
Fixation Time ◽  
Gaze Shift ◽  
The Gaze ◽  
Face Images ◽  
Trial Experience ◽  
Short Period ◽  
The Face ◽  
Gaze Cues

AbstractEye movements toward sequentially presented face images with or without gaze cues were recorded to investigate whether those with ASD, in comparison to their typically developing (TD) peers, could prospectively perform the task according to gaze cues. Line-drawn face images were sequentially presented for one second each on a laptop PC display, and the face images shifted from side-to-side and up-and-down. In the gaze cue condition, the gaze of the face image was directed to the position where the next face would be presented. Although the participants with ASD looked less at the eye area of the face image than their TD peers, they could perform comparable smooth gaze shift to the gaze cue of the face image in the gaze cue condition. This appropriate gaze shift in the ASD group was more evident in the second half of trials in than in the first half, as revealed by the mean proportion of fixation time in the eye area to valid gaze data in the early phase (during face image presentation) and the time to first fixation on the eye area. These results suggest that individuals with ASD may benefit from the short-period trial experiment by enhancing the usage of gaze cue.

scholarly journals Hybrid Attention Cascade Network for Facial Expression Recognition

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 2003 ◽  
Author(s):  
Xiaoliang Zhu ◽  
Shihao Ye ◽  
Liang Zhao ◽  
Zhicheng Dai
Keyword(s):  
Facial Expression ◽  
Facial Expressions ◽  
Facial Expression Recognition ◽  
Expression Recognition ◽  
Spatial Features ◽  
Face Images ◽  
Temporal Features ◽  
The Face ◽  
In The Wild ◽  
Fusion Features

As a sub-challenge of EmotiW (the Emotion Recognition in the Wild challenge), how to improve performance on the AFEW (Acted Facial Expressions in the wild) dataset is a popular benchmark for emotion recognition tasks with various constraints, including uneven illumination, head deflection, and facial posture. In this paper, we propose a convenient facial expression recognition cascade network comprising spatial feature extraction, hybrid attention, and temporal feature extraction. First, in a video sequence, faces in each frame are detected, and the corresponding face ROI (range of interest) is extracted to obtain the face images. Then, the face images in each frame are aligned based on the position information of the facial feature points in the images. Second, the aligned face images are input to the residual neural network to extract the spatial features of facial expressions corresponding to the face images. The spatial features are input to the hybrid attention module to obtain the fusion features of facial expressions. Finally, the fusion features are input in the gate control loop unit to extract the temporal features of facial expressions. The temporal features are input to the fully connected layer to classify and recognize facial expressions. Experiments using the CK+ (the extended Cohn Kanade), Oulu-CASIA (Institute of Automation, Chinese Academy of Sciences) and AFEW datasets obtained recognition accuracy rates of 98.46%, 87.31%, and 53.44%, respectively. This demonstrated that the proposed method achieves not only competitive performance comparable to state-of-the-art methods but also greater than 2% performance improvement on the AFEW dataset, proving the significant outperformance of facial expression recognition in the natural environment.

scholarly journals ROBUST THERMAL FACE RECOGNITION USING REGION CLASSIFIERS

2014 ◽  
Vol 28 (05) ◽  
pp. 1456008 ◽  
Author(s):  
AYAN SEAL ◽  
DEBOTOSH BHATTACHARJEE ◽  
MITA NASIPURI ◽  
CONSUELO GONZALO-MARTIN
Keyword(s):  
Recognition Performance ◽  
Singular Value ◽  
Majority Voting ◽  
Face Database ◽  
Identification Process ◽  
Decision Level ◽  
Face Images ◽  
Thermal Face ◽  
Value Decomposition ◽  
Level Fusion

This paper presents a robust approach for recognition of thermal face images based on decision level fusion of 34 different region classifiers. The region classifiers concentrate on local variations. They use singular value decomposition (SVD) for feature extraction. Fusion of decisions of the region classifier is done by using majority voting technique. The algorithm is tolerant against false exclusion of thermal information produced by the presence of inconsistent distribution of temperature statistics which generally make the identification process difficult. The algorithm is extensively evaluated on UGC-JU thermal face database, and Terravic facial infrared database and the recognition performance are found to be 95.83% and 100%, respectively. A comparative study has also been made with the existing works in the literature.

Virus induced hepatocellular carcinoma (HCC) and protein biomarkers

2021 ◽  
Author(s):  
Hamza Abbas Jaffari ◽  
Sumaira Mazhar
Keyword(s):  
Hepatocellular Carcinoma ◽  
Early Stage ◽  
Imaging Techniques ◽  
Disease Diagnosis ◽  
Protein Biomarkers ◽  
Early Disease ◽  
Detection Systems ◽  
Non Invasive ◽  
Viral Hepatitis B ◽  
Current Article

Hepatocellular carcinoma (HCC) is a standout amongst the most widely recognized cancers around the world, and just as the alcoholic liver disease it is also progressed by extreme viral hepatitis B or C. At the early stage of the disease, numerous patients are asymptomatic consequently late diagnosis of HCC occurs resulting in expensive surgical resection or transplantation. On the basis of the alpha fetoprotein (AFP) estimation, combined with the ultrasound and other sensitive imaging techniques used, the non-invasive detection systems are available. For early disease diagnosis and its use in the effective treatment of HCC patients, the identification of HCC biomarkers has provided a breakthrough utilizing the molecular genetics and proteomics. In the current article, most recent reports on the protein biomarkers of HBV or HCV-related HCC and their co-evolutionary association with liver cancer are reviewed.

Sign in / Sign up

Export Citation Format

Share Document