Journal articles: 'Thermal face images'

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Mostafa, Eslam, Riad Hammoud, Asem Ali, and Aly Farag. "Face recognition in low resolution thermal images." Computer Vision and Image Understanding 117, no. 12 (December 2013): 1689–94. http://dx.doi.org/10.1016/j.cviu.2013.07.010.

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Albar, Albar, Hendrick Hendrick, and Rahmad Hidayat. "Segmentation Method for Face Modelling in Thermal Images." Knowledge Engineering and Data Science 3, no. 2 (December 31, 2020): 99. http://dx.doi.org/10.17977/um018v3i22020p99-105.

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Face detection is mostly applied in RGB images. The object detection usually applied the Deep Learning method for model creation. One method face spoofing is by using a thermal camera. The famous object detection methods are Yolo, Fast RCNN, Faster RCNN, SSD, and Mask RCNN. We proposed a segmentation Mask RCNN method to create a face model from thermal images. This model was able to locate the face area in images. The dataset was established using 1600 images. The images were created from direct capturing and collecting from the online dataset. The Mask RCNN was configured to train with 5 epochs and 131 iterations. The final model predicted and located the face correctly using the test image.

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Quan, Yan Ming, Hao Xu, and Zhi Yong Ke. "Temperature Field Measurement of Turning Tool with Thermal Infrared Imager." Advanced Materials Research 305 (July 2011): 265–68. http://dx.doi.org/10.4028/www.scientific.net/amr.305.265.

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The variety of surface emissivity of carbide insert P10 against temperature raise is calibrated with antitheses. The influence of high temperature object near the carbide insert and the open measurement environment of the thermal infrared imager on the calibrated values are investigated. Then the thermal images of turning tool’s rake face are continuously captured by an infrared imager in the designed turning experiment. In the analysis of thermal images, the influence of measurement environment is taken into consideration and varied emissivity values are used to analyze the temperature in different areas of the rake face. A series of measurement results of temperature field in the rake face are achieved and they are consistent with the conventional rules of turning researches.

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Kanmani, Madheswari, and Venkateswaran Narasimhan. "Optimal fusion aided face recognition from visible and thermal face images." Multimedia Tools and Applications 79, no. 25-26 (February 24, 2020): 17859–83. http://dx.doi.org/10.1007/s11042-020-08628-9.

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Nagumo, Kent, Tomohiro Kobayashi, Kosuke Oiwa, and Akio Nozawa. "Face Alignment in Thermal Infrared Images Using Cascaded Shape Regression." International Journal of Environmental Research and Public Health 18, no. 4 (February 12, 2021): 1776. http://dx.doi.org/10.3390/ijerph18041776.

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The evaluation of physiological and psychological states using thermal infrared images is based on the skin temperature of specific regions of interest, such as the nose, mouth, and cheeks. To extract the skin temperature of the region of interest, face alignment in thermal infrared images is necessary. To date, the Active Appearance Model (AAM) has been used for face alignment in thermal infrared images. However, computation using this method is costly, and it has a low real-time performance. Conversely, face alignment of visible images using Cascaded Shape Regression (CSR) has been reported to have high real-time performance. However, no studies have been reported on face alignment in thermal infrared images using CSR. Therefore, the objective of this study was to verify the speed and robustness of face alignment in thermal infrared images using CSR. The results suggest that face alignment using CSR is more robust and computationally faster than AAM.

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Chame, Kanchan P. "Face Recognition using Sketch, Thermal and Infrared Images." International Journal for Research in Applied Science and Engineering Technology 9, no. 1 (January 31, 2021): 178–90. http://dx.doi.org/10.22214/ijraset.2021.32751.

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Grudzień, Artur, Marcin Kowalski, and Norbert Pałka. "Thermal Face Verification through Identification." Sensors 21, no. 9 (May 10, 2021): 3301. http://dx.doi.org/10.3390/s21093301.

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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.

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Hermosilla, Gabriel, José Luis Verdugo, Gonzalo Farias, Esteban Vera, Francisco Pizarro, and Margarita Machuca. "Face Recognition and Drunk Classification Using Infrared Face Images." Journal of Sensors 2018 (2018): 1–8. http://dx.doi.org/10.1155/2018/5813514.

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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.

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Sancen-Plaza, Agustin, Luis M. Contreras-Medina, Alejandro Israel Barranco-Gutiérrez, Carlos Villaseñor-Mora, Juan J. Martínez-Nolasco, and José A. Padilla-Medina. "Facial Recognition for Drunk People Using Thermal Imaging." Mathematical Problems in Engineering 2020 (April 14, 2020): 1–9. http://dx.doi.org/10.1155/2020/1024173.

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Face recognition using thermal imaging has the main advantage of being less affected by lighting conditions compared to images in the visible spectrum. However, there are factors such as the process of human thermoregulation that cause variations in the surface temperature of the face. These variations cause recognition systems to lose effectiveness. In particular, alcohol intake causes changes in the surface temperature of the face. It is of high relevance to identify not only if a person is drunk but also their identity. In this paper, we present a technique for face recognition based on thermal face images of drunk people. For the experiments, the Pontificia Universidad Católica de Valparaíso-Drunk Thermal Face database (PUCV-DTF) was used. The recognition system was carried out by using local binary patterns (LBPs). The LBP features were obtained from the bioheat model from thermal image representation and a fusion of thermal images and a vascular network extracted from the same image. The feature vector for each image is formed by the concatenation of the LBP histogram of the thermogram with an anisotropic filter and the fused image, respectively. The proposed technique has an average percentage of 99.63% in the Rank-10 cumulative classification; this performance is superior compared to using LBP in thermal images that do not use the bioheat model.

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Fitriyah, Hurriyatul, Edita Rosana Widasari, and Rekyan Regasari Mardi Putri. "Inner-Canthus Localization of Thermal Images in Face-View Invariant." International Journal on Advanced Science, Engineering and Information Technology 8, no. 6 (December 4, 2018): 2570. http://dx.doi.org/10.18517/ijaseit.8.5.3903.

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Fitriyah, Hurriyatul, Edita Rosana Widasari, and Rekyan Regasari Mardi Putri. "Inner-Canthus Localization of Thermal Images in Face-View Invariant." International Journal on Advanced Science, Engineering and Information Technology 8, no. 6 (December 4, 2018): 2570. http://dx.doi.org/10.18517/ijaseit.8.6.3903.

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Matsuno, Shogo, Tota Mizuno, Hirotoshi Asano, Kazuyuki Mito, and Naoaki Itakura. "Estimating autonomic nerve activity using variance of thermal face images." Artificial Life and Robotics 23, no. 3 (June 4, 2018): 367–72. http://dx.doi.org/10.1007/s10015-018-0436-z.

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Kim, Sa-Mun, Dae-Jong Lee, Ho-Hyun Lee, and Myung-Geun Chun. "Person Recognition Using Gait and Face Features on Thermal Images." Transactions of the Korean Institute of Electrical Engineers P 65, no. 2 (June 1, 2016): 130–35. http://dx.doi.org/10.5370/kieep.2016.65.2.130.

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Seal, Ayan, Debotosh Bhattacharjee, Mita Nasipuri, Consuelo Gonzalo-Martin, and Ernestina Menasalvas. "Fusion of Visible and Thermal Images Using a Directed Search Method for Face Recognition." International Journal of Pattern Recognition and Artificial Intelligence 31, no. 04 (February 2, 2017): 1756005. http://dx.doi.org/10.1142/s0218001417560055.

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A new image fusion algorithm based on the visible and thermal images for face recognition is presented in this paper. The new fusion algorithm derives the benefit from both the modalities images. The proposed fusion process is the weighted sum of thermal and visible face information with two weighting factors [Formula: see text] and [Formula: see text], respectively. The weighting factors are calculated using a directed search algorithm automatically. The proposed fusion framework is evaluated through extensive experiments using UGC-JU face database. Experiments are of three fold. Firstly, individual modalities images are used separately for human face recognition. Secondly, fused face images using the proposed method are used for recognition purpose. The highest level of accuracy achieved by using the proposed method is about 98.42%. Lastly, the three existing fusion methods are applied on the same face database for comparison with the results of the proposed method. All the results demonstrate significant performance improvements in recognition over individual modalities and some of the existing fusion approaches, suggesting that fusion is a viable approach that deserves further study and consideration.

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Bhattacharjee, Debotosh, Ayan Seal, Suranjan Ganguly, Mita Nasipuri, and Dipak Kumar Basu. "A Comparative Study of Human Thermal Face Recognition Based on Haar Wavelet Transform and Local Binary Pattern." Computational Intelligence and Neuroscience 2012 (2012): 1–12. http://dx.doi.org/10.1155/2012/261089.

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Thermal infrared (IR) images focus on changes of temperature distribution on facial muscles and blood vessels. These temperature changes can be regarded as texture features of images. A comparative study of face two recognition methods working in thermal spectrum is carried out in this paper. In the first approach, the training images and the test images are processed with Haar wavelet transform and the LL band and the average of LH/HL/HH bands subimages are created for each face image. Then a total confidence matrix is formed for each face image by taking a weighted sum of the corresponding pixel values of the LL band and average band. For LBP feature extraction, each of the face images in training and test datasets is divided into 161 numbers of subimages, each of size 8 × 8 pixels. For each such subimages, LBP features are extracted which are concatenated in manner. PCA is performed separately on the individual feature set for dimensionality reduction. Finally, two different classifiers namely multilayer feed forward neural network and minimum distance classifier are used to classify face images. The experiments have been performed on the database created at our own laboratory and Terravic Facial IR Database.

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SEAL, AYAN, DEBOTOSH BHATTACHARJEE, MITA NASIPURI, and CONSUELO GONZALO-MARTIN. "ROBUST THERMAL FACE RECOGNITION USING REGION CLASSIFIERS." International Journal of Pattern Recognition and Artificial Intelligence 28, no. 05 (July 31, 2014): 1456008. http://dx.doi.org/10.1142/s0218001414560084.

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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.

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Fitriyah, Hurriyatul, and Edita Rosana Widasari. "Face Detection of Thermal Images in Various Standing Body-Pose using Facial Geometry." IJCCS (Indonesian Journal of Computing and Cybernetics Systems) 14, no. 4 (October 31, 2020): 407. http://dx.doi.org/10.22146/ijccs.59672.

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Automatic face detection in frontal view for thermal images is a primary task in a health system e.g. febrile identification or security system e.g. intruder recognition. In a daily state, the scanned person does not always stay in frontal face view. This paper develops an algorithm to identify a frontal face in various standing body-pose. The algorithm used an image processing method where first it segmented face based on human skin’s temperature. Some exposed non-face body parts could also get included in the segmentation result, hence discriminant features of a face were applied. The shape features were based on the characteristic of a frontal face, which are: (1) Size of a face, (2) facial Golden Ratio, and (3) Shape of a face is oval. The algorithm was tested on various standing body-pose that rotate 360° towards 2 meters and 4 meters camera-to-object distance. The accuracy of the algorithm on face detection in a manageable environment is 95.8%. It detected face whether the person was wearing glasses or not.

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Pavlovic, Milos, Branka Stojanovic, Ranko Petrovic, Snezana Puzovic, and Srdjan Stankovic. "Optimal hog cell to image ratio for robust multi-sensor face recognition systems." Serbian Journal of Electrical Engineering 16, no. 3 (2019): 387–403. http://dx.doi.org/10.2298/sjee1903387p.

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The main problem for modern visible light face recognition has been accurate identification under variable environmental conditions. Thermal infrared facial images utilization in face recognition systems can provide a solution for problems related to uncontrolled environmental conditions, especially to those caused by illumination limitations. This paper compares the results of the use of visible light and thermal infrared imagery for face recognition based on the HOG feature descriptor. In particular, the paper suggests an optimal HOG cell to image size ratio in order to improve recognition accuracy and reduce computational complexity. Performance statistics are presented on facial images with different facial expressions. The obtained results support the conclusion that recognition with thermal infrared images is more robust and that fusion of sensors should be included for improving recognition accuracy.

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Seal, Ayan, and Chinmaya Panigrahy. "Human authentication based on fusion of thermal and visible face images." Multimedia Tools and Applications 78, no. 21 (May 20, 2019): 30373–95. http://dx.doi.org/10.1007/s11042-019-7701-6.

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Marzec, Mariusz, Robert Koprowski, Zygmunt Wróbel, Agnieszka Kleszcz, and Sławomir Wilczyński. "Automatic method for detection of characteristic areas in thermal face images." Multimedia Tools and Applications 74, no. 12 (October 31, 2013): 4351–68. http://dx.doi.org/10.1007/s11042-013-1745-9.

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Cho, Se, Na Baek, Min Kim, Ja Koo, Jong Kim, and Kang Park. "Face Detection in Nighttime Images Using Visible-Light Camera Sensors with Two-Step Faster Region-Based Convolutional Neural Network." Sensors 18, no. 9 (September 7, 2018): 2995. http://dx.doi.org/10.3390/s18092995.

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Conventional nighttime face detection studies mostly use near-infrared (NIR) light cameras or thermal cameras, which are robust to environmental illumination variation and low illumination. However, for the NIR camera, it is difficult to adjust the intensity and angle of the additional NIR illuminator according to its distance from an object. As for the thermal camera, it is expensive to use as a surveillance camera. For these reasons, we propose a nighttime face detection method based on deep learning using a single visible-light camera. In a long-distance night image, it is difficult to detect faces directly from the entire image due to noise and image blur. Therefore, we propose Two-Step Faster region-based convolutional neural network (R-CNN) based on the image preprocessed by histogram equalization (HE). As a two-step scheme, our method sequentially performs the detectors of body and face areas, and locates the face inside a limited body area. By using our two-step method, the processing time by Faster R-CNN can be reduced while maintaining the accuracy of face detection by Faster R-CNN. Using a self-constructed database called Dongguk Nighttime Face Detection database (DNFD-DB1) and an open database of Fudan University, we proved that the proposed method performs better compared to other existing face detectors. In addition, the proposed Two-Step Faster R-CNN outperformed single Faster R-CNN and our method with HE showed higher accuracies than those without our preprocessing in nighttime face detection.

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Sun, Pengcheng, Dan Zeng, Xiaoyan Li, Lin Yang, Liyuan Li, Zhouxia Chen, and Fansheng Chen. "A 3D Mask Presentation Attack Detection Method Based on Polarization Medium Wave Infrared Imaging." Symmetry 12, no. 3 (March 3, 2020): 376. http://dx.doi.org/10.3390/sym12030376.

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Facial recognition systems are often spoofed by presentation attack instruments (PAI), especially by the use of three-dimensional (3D) face masks. However, nonuniform illumination conditions and significant differences in facial appearance will lead to the performance degradation of existing presentation attack detection (PAD) methods. Based on conventional thermal infrared imaging, a PAD method based on the medium wave infrared (MWIR) polarization characteristics of the surface material is proposed in this paper for countering a flexible 3D silicone mask presentation attack. A polarization MWIR imaging system for face spoofing detection is designed and built, taking advantage of the fact that polarization-based MWIR imaging is not restricted by external light sources (including visible light and near-infrared light sources) in spite of facial appearance. A sample database of real face images and 3D face mask images is constructed, and the gradient amplitude feature extraction method, based on MWIR polarization facial images, is designed to better distinguish the skin of a real face from the material used to make a 3D mask. Experimental results show that, compared with conventional thermal infrared imaging, polarization-based MWIR imaging is more suitable for the PAD method of 3D silicone masks and shows a certain robustness in the change of facial temperature.

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Kong, Seong G., Jingu Heo, Faysal Boughorbel, Yue Zheng, Besma R. Abidi, Andreas Koschan, Mingzhong Yi, and Mongi A. Abidi. "Multiscale Fusion of Visible and Thermal IR Images for Illumination-Invariant Face Recognition." International Journal of Computer Vision 71, no. 2 (June 1, 2006): 215–33. http://dx.doi.org/10.1007/s11263-006-6655-0.

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Hermosilla, Gabriel, Gonzalo Farias, Cesar San Martin, and Francisco Gallardo. "Study of Local Matching-Based Facial Recognition Methods Using Thermal Infrared Imagery." International Journal of Pattern Recognition and Artificial Intelligence 29, no. 08 (November 22, 2015): 1556012. http://dx.doi.org/10.1142/s0218001415560121.

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This paper shows a comparative study among different local matching-based methods for thermal infrared face recognition. The principal assumption of this work is that the thermal face corresponds to the diffuse energy emission captured by an infrared camera, where the thermal signature is unique for each subject and it can be addressed as a texture descriptor with thermal images. Local matching-based methods find inter-class differences that improve the face recognition rate in thermal spectrum. Specifically, this work considers four methods: Local Binary Pattern (LBP), Local Derivative Pattern (LDP), Weber Linear Descriptor (WLD) and Histograms of Oriented Gradients Descriptors (HOG). The methods are evaluated and compared using the UCHThermalFace database, that considers real-world conditions and unconstrained environments, such as indoor and outdoor setups, natural variations in illumination, facial expression, pose, accessories, occlusions, and background. Results indicate that HOG variants followed by LBP method achieved the best recognition rates for face recognition systems.

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Yoshikawa, Hiroki, Akira Uchiyama, and Teruo Higashino. "ThermalWrist: Smartphone Thermal Camera Correction Using a Wristband Sensor †." Sensors 19, no. 18 (September 4, 2019): 3826. http://dx.doi.org/10.3390/s19183826.

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Thermal images are widely used for various healthcare applications and advanced research. However, thermal images captured by smartphone thermal cameras are not accurate for monitoring human body temperature due to the small body that is vulnerable to temperature change. In this paper, we propose ThermalWrist, a dynamic offset correction method for thermal images captured by smartphone thermal cameras. We fully utilize the characteristic that is specific to thermal cameras: the relative temperatures in a single thermal image are highly reliable, although the absolute temperatures fluctuate frequently. To correct the offset error, ThermalWrist combines thermal images with a reliable absolute temperature obtained by a wristband sensor based on the above characteristic. The evaluation results in an indoor air-conditioned environment shows that the mean absolute error and the standard deviation of face temperature measurement error decrease by 49.4% and 64.9%, respectively. In addition, Pearson’s correlation coefficient increases by 112%, highlighting the effectiveness of ThermalWrist. We also investigate the limitation with respect to the ambient temperature where ThermalWrist works effectively. The result shows ThermalWrist works well in the normal office environment, which is 22.91 °C and above.

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van Doremalen, Rob F. M., Jaap J. van Netten, Jeff G. van Baal, Miriam M. R. Vollenbroek-Hutten, and Ferdinand van der Heijden. "Infrared 3D Thermography for Inflammation Detection in Diabetic Foot Disease: A Proof of Concept." Journal of Diabetes Science and Technology 14, no. 1 (June 14, 2019): 46–54. http://dx.doi.org/10.1177/1932296819854062.

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Background: Thermal assessment of the plantar surface of the foot using spot thermometers and thermal imaging has been proven effective in diabetic foot ulcer prevention. However, with traditional cameras this is limited to single spots or a two-dimensional (2D) view of the plantar side of foot, where only 50% of the ulcers occur. To improve ulcer detection, the view has to be extended beyond 2D. Our aim is to explore for proof of concept the combination of three-dimensional (3D) models with thermal imaging for inflammation detection in diabetic foot disease. Method: From eight participants with a current diabetic foot ulcer we simultaneously acquired a 3D foot model and three thermal infrared images using a high-resolution medical 3D imaging system aligned with three smartphone-based thermal infrared cameras. Using spatial transformations, we aimed to map thermal images onto the 3D model, to create the 3D visualizations. Expert clinicians assessed these for quality and face validity as +, +/-, -. Results: We could replace the texture maps (color definitions) of the 3D model with the thermal infrared images and created the first-ever 3D thermographs of the diabetic foot. We then converted these models to 3D PDF-files compatible with the hospital IT environment. Face validity was assessed as + in six and +/- in two cases. Conclusions: We have provided a proof of concept for the creation of clinically useful 3D thermal foot images to assess the diabetic foot skin temperature in 3D in a hospital IT environment. Future developments are expected to improve the image-processing techniques to result in easier, handheld applications and driving further research.

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Hahn, Amanda C., Ross D. Whitehead, Marion Albrecht, Carmen E. Lefevre, and David I. Perrett. "Hot or not? Thermal reactions to social contact." Biology Letters 8, no. 5 (May 30, 2012): 864–67. http://dx.doi.org/10.1098/rsbl.2012.0338.

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Previous studies using thermal imaging have suggested that face and body temperature increase during periods of sexual arousal. Additionally, facial skin temperature changes are associated with other forms of emotional arousal, including fear and stress. This study investigated whether interpersonal social contact can elicit facial temperature changes. Study 1: infrared images were taken during a standardized interaction with a same- and opposite-sex experimenter using skin contact in a number of potentially high–intimate (face and chest) and low–intimate (arm and palm) locations. Facial skin temperatures significantly increased from baseline during the face and chest contact, and these temperature shifts were larger when contact was made by an opposite-sex experimenter. Study 2: the topography of facial temperature change was investigated in five regions: forehead, periorbital, nose, mouth and cheeks. Increased temperature in the periorbital, nose and mouth regions predicted overall facial temperature shifts to social contact. Our findings demonstrate skin temperature changes are a sensitive index of arousal during interpersonal interactions.

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Li, Dong, Lu, Lou, and Zhou. "Multi-Sensor Face Registration Based on Global and Local Structures." Applied Sciences 9, no. 21 (October 30, 2019): 4623. http://dx.doi.org/10.3390/app9214623.

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The work reported in this paper aims at utilizing the global geometrical relationship and local shape feature to register multi-spectral images for fusion-based face recognition. We first propose a multi-spectral face images registration method based on both global and local structures of feature point sets. In order to combine the global geometrical relationship and local shape feature in a new Student’s t Mixture probabilistic model framework. On the one hand, we use inner-distance shape context as the local shape descriptors of feature point sets. On the other hand, we formulate the feature point sets registration of the multi-spectral face images as the Student’s t Mixture probabilistic model estimation, and local shape descriptors are used to replace the mixing proportions of the prior Student’s t Mixture Model. Furthermore, in order to improve the anti-interference performance of face recognition techniques, a guided filtering and gradient preserving image fusion strategy is used to fuse the registered multi-spectral face image. It can make the multi-spectral fusion image hold more apparent details of the visible image and thermal radiation information of the infrared image. Subjective and objective registration experiments are conducted with manual selected landmarks and real multi-spectral face images. The qualitative and quantitative comparisons with the state-of-the-art methods demonstrate the accuracy and robustness of our proposed method in solving the multi-spectral face image registration problem.

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Bhowmik, Mrinal Kanti. "Eye region-based fusion technique of thermal and dark visual images for human face recognition." Optical Engineering 51, no. 7 (July 9, 2012): 077205. http://dx.doi.org/10.1117/1.oe.51.7.077205.

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Litvin, Andre, Kamal Nasrollahi, Sergio Escalera, Cagri Ozcinar, Thomas B. Moeslund, and Gholamreza Anbarjafari. "A novel deep network architecture for reconstructing RGB facial images from thermal for face recognition." Multimedia Tools and Applications 78, no. 18 (May 24, 2019): 25259–71. http://dx.doi.org/10.1007/s11042-019-7667-4.

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Rao, M. Sivasankara, K. Tejasree, P. Sathwik, P. Sandeep Kumar, and M. Sailohith. "Real Time Face Mask Detection and Thermal Screening with Audio Response for COVID-19." Revista Gestão Inovação e Tecnologias 11, no. 4 (July 22, 2021): 2703–14. http://dx.doi.org/10.47059/revistageintec.v11i4.2311.

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The coronavirus COVID-19 pandemic is continuously spreading until now everywhere on the earth, and causing a severe health crisis. So the helpful and safe-keeping method is wearing a face mask in all areas where people are gathered, according to the World Health Organization (WHO). Along with the face mask, body temperature and sanitization also plays a vital role in being safer. Thus, monitoring the individuals that are wearing the mask or not is more significant. In this paper, we propose a system that uses TensorFlow, Keras, MobileNetV2, and OpenCV to detect the face mask. A dataset contains images of persons with and without masks obtained from multiple sources and trained on a deep learning model. Then the automatic temperature checking and Sanitation are done. Finally, the proposed system gives an audio/voice output whether the face mask is present or not, the person's body temperature. Our approach would be beneficial in reducing the spread of this infectious disease and will encourage people to use face masks, getting regularly sanitized and monitoring the temperature can keep the workplace safe.

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Chen, Cunjian, and Arun Ross. "Matching thermal to visible face images using hidden factor analysis in a cascaded subspace learning framework." Pattern Recognition Letters 72 (March 2016): 25–32. http://dx.doi.org/10.1016/j.patrec.2015.06.021.

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Kakaraparthi, Vimal, Qijia Shao, Charles J. Carver, Tien Pham, Nam Bui, Phuc Nguyen, Xia Zhou, and Tam Vu. "FaceSense." Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 5, no. 3 (September 9, 2021): 1–27. http://dx.doi.org/10.1145/3478129.

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Face touch is an unconscious human habit. Frequent touching of sensitive/mucosal facial zones (eyes, nose, and mouth) increases health risks by passing pathogens into the body and spreading diseases. Furthermore, accurate monitoring of face touch is critical for behavioral intervention. Existing monitoring systems only capture objects approaching the face, rather than detecting actual touches. As such, these systems are prone to false positives upon hand or object movement in proximity to one's face (e.g., picking up a phone). We present FaceSense, an ear-worn system capable of identifying actual touches and differentiating them between sensitive/mucosal areas from other facial areas. Following a multimodal approach, FaceSense integrates low-resolution thermal images and physiological signals. Thermal sensors sense the thermal infrared signal emitted by an approaching hand, while physiological sensors monitor impedance changes caused by skin deformation during a touch. Processed thermal and physiological signals are fed into a deep learning model (TouchNet) to detect touches and identify the facial zone of the touch. We fabricated prototypes using off-the-shelf hardware and conducted experiments with 14 participants while they perform various daily activities (e.g., drinking, talking). Results show a macro-F1-score of 83.4% for touch detection with leave-one-user-out cross-validation and a macro-F1-score of 90.1% for touch zone identification with a personalized model.

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Suzuki, Takuma, Hirotaka Yamaguchi, Tetsuo Hatakeyama, Hirofumi Matsuhata, Junji Senzaki, Kenji Fukuda, Takashi Shinohe, and Hajime Okumura. "Effects of Surface Morphological Defects and Crystallographic Defects on Reliability of Thermal Oxides on C-Face." Materials Science Forum 717-720 (May 2012): 789–92. http://dx.doi.org/10.4028/www.scientific.net/msf.717-720.789.

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The causes of extrinsic failures in time-dependent dielectric breakdown characteristics of gate oxide on C-face of 4H-SiC are examined by comparing breakdown points of tested gate oxides with the images of X-ray topography and those of differential interference contrast microscopy. We have concluded as follows: (1) surface morphological defects that originate from threading screw dislocations degrade reliability of gate oxides. (2) These surface defects are not necessarily found on every wafer. (3) Crystallographic defects are not killer defects of MOSFET per se.

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Rodriguez-Lozano, Francisco J., Fernando León-García, M. Ruiz de Adana, Jose M. Palomares, and J. Olivares. "Non-Invasive Forehead Segmentation in Thermographic Imaging." Sensors 19, no. 19 (September 22, 2019): 4096. http://dx.doi.org/10.3390/s19194096.

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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.

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Budzan, Sebastian, and Roman Wyżgolik. "Face and eyes localization algorithm in thermal images for temperature measurement of the inner canthus of the eyes." Infrared Physics & Technology 60 (September 2013): 225–34. http://dx.doi.org/10.1016/j.infrared.2013.05.007.

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Gasparro, Roberta, Grazia Leonetti, Michele Riccio, Andrea Irace, Gilberto Sammartino, Andrea Blasi, Cristiano Scandurra, Nelson Mauro Maldonato, Pasquale Sammartino, and Gaetano Marenzi. "Thermography as a Method to Detect Dental Anxiety in Oral Surgery." Applied Sciences 11, no. 12 (June 10, 2021): 5421. http://dx.doi.org/10.3390/app11125421.

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(1) Background: the aim of this study was to evaluate if dental anxiety can be measured objectively using thermal infrared imaging. (2) Methods: Patients referred to the Department of Oral Surgery of the University of Naples Federico II and requiring dental extractions were consecutively enrolled in the study. Face thermal distribution images of the patients were acquired before and during their first clinical examination using infrared thermal cameras. The data were analyzed in relation to five regions of interest (ROI) of the patient’s face (nose, ear, forehead, zygoma, chin). The differences in the temperatures assessed between the two measurements for each ROI were evaluated by using paired T-test. The Pearson correlation and linear regression were performed to evaluate the association between differences in temperatures and Modified Dental Anxiety Scale (MDAS) questionnaire score, age, and gender; (3) results: sixty participants were enrolled in the study (28 males and 32 females; mean age 57.4 year-old; age range 18–80 year-old). Only for nose and ear zone there was a statistically significant difference between measurements at baseline and visit. Correlation between the thermal imaging measurements and the scores of the MDAS questionnaire was found for nose and ear, but not for all of the other regions. (4) Conclusions: the study demonstrated a potential use of thermal infrared imaging to measure dental anxiety.

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Seal, Ayan, Debotosh Bhattacharjee, and Mita Nasipuri. "Human face recognition using random forest based fusion of à-trous wavelet transform coefficients from thermal and visible images." AEU - International Journal of Electronics and Communications 70, no. 8 (August 2016): 1041–49. http://dx.doi.org/10.1016/j.aeue.2016.04.016.

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Jamrozik, Wojciech, and Jacek Górka. "Detection of slag inclusions using infrared thermal imagining system." MATEC Web of Conferences 338 (2021): 01012. http://dx.doi.org/10.1051/matecconf/202133801012.

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Assuring high quality of welded joins is a vital task in many industrial branches also when joints are made manually. It is the case metal-arc welding with covered electrode. One of main imperfection, that can occur in this process is slag inclusion. In the paper an method for detection of slag inclusion in multipass manual welding is proposed and validated. The key idea of the method is that small temperature disturbances will be noticeable in consecutive cross-section of joint in the cooling pass. Temperature distribution weld face was measured with longwave infrared camera (LWIR). For consecutive cross-section made in IR representation of joint differences in mean temperature was calculated to assess the cooling rate directly after the elements were welded. It can be made because on each thermogram the whole joint is visible, thus position of electrode in time can be easily marked. Results of slag inclusion detection were compared with radiographic images of made joints. In the future additional studies will be performed in order to generalize proposed method to wider group of materials and for more complex welds.

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Wei, Wei, Jian Wei Yu, Tao You, Xiao Fen Yu, and Yong Hong Wang. "Evaluation of the Transient Temperature Distribution of End-Face Sliding Friction Pair Using Infrared Thermometry." Key Engineering Materials 613 (May 2014): 213–18. http://dx.doi.org/10.4028/www.scientific.net/kem.613.213.

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A real-time temperature measurement system was designed for end-face sliding friction pairs with an infrared (IR) probe and IR thermography installed on it. The approximate temperature of contact surface was measured by the probe while non-contact surface’s temperature distribution was determined with the IR thermography. Two experiments with constant load but varied rotational speeds were carried out, and a preliminary study was made to analyze the variation of temperature in the friction process. Furthermore, the probe data was used as thermal load to calculate the temperature field by the FEM model and the result was verified using IR images. The experimental results showed that the infrared measurement system can detect and record the interface-temperature variation accurately. The probe data showed a good dynamic performance with the variation of friction coefficient. In addition, the calculated temperature field showed good accordance with the IR thermography data.

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Delgado, Cristina, Vitor Gonçalves, Saúl Blanco, and Salomé F. P. Almeida. "A new diatom (Bacillariophyceae) species from a thermal spring in Azores archipelago (São Miguel island, Atlantic Ocean)." Botanical Sciences 99, no. 1 (October 27, 2020): 169–81. http://dx.doi.org/10.17129/botsci.2680.

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Background: Due to their isolation, islands offer excellent areas for the study of distribution of benthic diatoms. On the other hand, diatoms bearing canal raphe have received less attention compared to other groups of diatoms such as Navicula, Pinnularia or Amphora. Questions: Is it possible that thermal springs on islands offer a refuge for infrequent diatom species? Studied species: Platichthys furnensis C. Delgado, V. Gonçalves & S.F.P. Almeida sp. nov. Study site and dates: The species here described was collected in the epilithon of a thermal spring in São Miguel Island (Azores Archipelago, Portugal) in September 2015. Methods: This new taxon was compared to other diatom species of the genera Nitzschia, Tryblionella, Entomoneis and Hantzschia and to the other species of the genus Platichthys. The morphology is documented by light and scanning electron images and discussed in detail. Results: Platichthys furnensis was found in a thermal pool, a similar habitat to the one where P. krammeri type was collected in Chile in 1940. P. furnensis has many structures that are characteristic of the recently described genus Platichthys, including raised canal raphe and fibulae, compressed valve face, steep valve face and numerous open copulae. Conclusions: The description of the new taxon is interesting because it is the first species within Platichthys to be described from the Northern Hemisphere.

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Zefri, Yahya, Achraf ElKettani, Imane Sebari, and Sara Ait Lamallam. "Thermal Infrared and Visual Inspection of Photovoltaic Installations by UAV Photogrammetry—Application Case: Morocco." Drones 2, no. 4 (November 23, 2018): 41. http://dx.doi.org/10.3390/drones2040041.

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Being sustainable, clean, and eco-friendly, photovoltaic technology is considered as one of the most hoped solutions face to worldwide energetic challenges. Morocco joins this context with the inauguration of numerous clean energy projects. However, one key factor in making photovoltaic installations a profitable investment are regular and effective inspections in order to detect occurred defects. Unmanned aerial vehicles (UAV) are increasingly used in various inspection fields. In this respect, this work focuses on the use of thermal and visual imagery taken by UAV in the inspection of photovoltaic installations. Visual and thermal images of photovoltaic modules, obtained by UAV, from different installations, and with different acquisition conditions and parameters, were exploited to generate orthomosaics for inspection purposes. The methodology was tested on a dataset we have acquired by a mission in Rabat (Morocco), and also on external datasets acquired in Switzerland. As final results, several visual defects were detected in visual RGB and thermal orthomosaics, such as cracks, soiling, and hotspots. In addition, a procedure of semi-automatic hotspots’ extraction was also developed and is presented within this work. On the other side, various tests were conducted on the influence of some acquisition and processing parameters (images’ overlap, the ground sampling distance, the flying height, the use of ground control points, the internal camera parameters’ optimization) on the detection of defects and the quality of visual and thermal generated orthomosaics. In the end, the potential of UAV thermal and visual imagery in the inspection of photovoltaic installations was discussed in function of various parameters. On the basis of the discussion feedback, UAV were concluded as advantageous tools within the thematic of this project, which proves the necessity of their implementation in this context.

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Samadiani, Huang, Cai, Luo, Chi, Xiang, and He. "A Review on Automatic Facial Expression Recognition Systems Assisted by Multimodal Sensor Data." Sensors 19, no. 8 (April 18, 2019): 1863. http://dx.doi.org/10.3390/s19081863.

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Facial Expression Recognition (FER) can be widely applied to various research areas, such as mental diseases diagnosis and human social/physiological interaction detection. With the emerging advanced technologies in hardware and sensors, FER systems have been developed to support real-world application scenes, instead of laboratory environments. Although the laboratory-controlled FER systems achieve very high accuracy, around 97%, the technical transferring from the laboratory to real-world applications faces a great barrier of very low accuracy, approximately 50%. In this survey, we comprehensively discuss three significant challenges in the unconstrained real-world environments, such as illumination variation, head pose, and subject-dependence, which may not be resolved by only analysing images/videos in the FER system. We focus on those sensors that may provide extra information and help the FER systems to detect emotion in both static images and video sequences. We introduce three categories of sensors that may help improve the accuracy and reliability of an expression recognition system by tackling the challenges mentioned above in pure image/video processing. The first group is detailed-face sensors, which detect a small dynamic change of a face component, such as eye-trackers, which may help differentiate the background noise and the feature of faces. The second is non-visual sensors, such as audio, depth, and EEG sensors, which provide extra information in addition to visual dimension and improve the recognition reliability for example in illumination variation and position shift situation. The last is target-focused sensors, such as infrared thermal sensors, which can facilitate the FER systems to filter useless visual contents and may help resist illumination variation. Also, we discuss the methods of fusing different inputs obtained from multimodal sensors in an emotion system. We comparatively review the most prominent multimodal emotional expression recognition approaches and point out their advantages and limitations. We briefly introduce the benchmark data sets related to FER systems for each category of sensors and extend our survey to the open challenges and issues. Meanwhile, we design a framework of an expression recognition system, which uses multimodal sensor data (provided by the three categories of sensors) to provide complete information about emotions to assist the pure face image/video analysis. We theoretically analyse the feasibility and achievability of our new expression recognition system, especially for the use in the wild environment, and point out the future directions to design an efficient, emotional expression recognition system.

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Dumke, M., and M. Krause. "Radio and Polarization Properties in the Disk and Halo of Edge-On Spirals." International Astronomical Union Colloquium 166 (1997): 555–58. http://dx.doi.org/10.1017/s0252921100071608.

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AbstractWe have observed a small sample of edge-on galaxies in total and linearly polarized radio continuum emission at λ6.2 cm, using the Effelsberg 100m telescope. The resulting maps were combined with available VLA data in order to obtain high-sensitivity radio images which have a sufficient angular resolution and do not suffer from the so-called missing-spacing problem.From an analysis of these images (together with 2.8cm and 20cm data) we get the following results: 1. The radio emission perpendicular to the plane can be described by a two-component exponential distribution with scale-heights of ~ 300 pc and ~ 1.8 kpc, independently of the star forming activity and interaction state. 2. In the disk of the non-interacting galaxies of our sample the thermal fraction of the emission seems to be higher than usually deduced from observations of face-on galaxies. 3. The fractional polarization p increases with increasing galactic height, reaches a maximum at h ~ 1 – 3 kpc, and decreases again. In general p is lower in actively star forming galaxies.

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Gene, Salahudeen A., Elias B. Saion, Abdul Halim Shaari, Mazliana A. Kamarudeen, and Naif Mohammed Al-Hada. "Fabrication and Characterization of Nanospinel ZnCr₂O₄ Using Thermal Treatement Method." Advanced Materials Research 1107 (June 2015): 301–7. http://dx.doi.org/10.4028/www.scientific.net/amr.1107.301.

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The fabrication of nanospinel zinc chromite (ZnCr2O4) crystals by the means of thermal treatment method from an aqueous solution containing metal nitrates, polyvinyl pyrrolidone (PVP), and deionized water was described in this study. The samples were calcined at various temperatures ranging from 773 to 973 K for the decomposition of the organic compounds and crystallization of the nanocrystals. PVP was used as capping agent to control the agglomeration of the particles. The characterization studies of the fabricated samples were carried out by X-ray diffraction spectroscopy (XRD), transmission electron microscopy (TEM), energy dispersed X-ray spectroscopy (EDX) and electron spin resonance spectroscopy (ESR). The corresponding peaks of Zn, Cr and O were observed in the EDX spectrum of the sample which confirms the formation of ZnCr2O4. The XRD patterns also confirmed the formation of the single faced nanocrystallines of spinel ZnCr2O4 with a face-centered cubic structure. The average particle size of the synthesized crystals was also determined from the XRD patterns using the Scherers formula which shows that the crystallite sizes increases with increase in calcination temperature and was in good agreement with the TEM images which shows cubical ZnCr2O4 nanocrystals with uniform morphology and particle size distributions. The ESR spectra confirmed the existence of unpaired electron in the fabricated samples and the increase in g-factor and decreases in resonant magnetic field (Hr) were observed as the calcination temperature increases.

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Ali, Salman, and Baofeng Li. "Evaluating the Impact of the Morphological Transformation of Urban Sites on the Urban Thermal Microenvironment." Buildings 8, no. 12 (December 18, 2018): 182. http://dx.doi.org/10.3390/buildings8120182.

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Tropical cities currently face issues of climate change resulting from rapid urbanization and the impact of urban morphological transformations on the microclimate. The analysis of urban physical forms and patterns is a realisticmethodfor quantifying these impacts. This work examined the impact of morphological transformations of an urban site in Wuhan, China, on the microthermal environment at different time periods. We also quantified and compared the impact of four urban site morphologies on ambient air temperature. The morphological changes of the study site were inferred from Google Earth images acquired at different time points in 2006 and 2013. ENVI-met simulation software was used to compare the changes in temperature at the selected site by specific date. The year- and time-based analysis of existing urban morphologies and their impact on the microurban thermal environment shows that the overall minimum and maximum values of morning and afternoon ambient air temperature are nearly the same for the 2013 and 2006 morphologies. The maximum temperature difference was observed in the afternoon (14:00), with an average difference of approximately 2 °C in the east. The findings of this research could provide a useful guide for optimizing the transformation of urban site planning and design and a suitable method for assessing the impact of built-up areas on the environment.

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Hossain, Mohammad Sharif, Muhammed Shah Miran, Md Rokonujjaman, Md Abu Bin Hasan Susan, M. Yousuf A. Mollah, and MM Rahman. "Synthesis of Nickel Nanoparticles Using Poly (Vinyl Alcohol) As A Capping Agent." Journal of the Asiatic Society of Bangladesh, Science 40, no. 2 (December 30, 2014): 197–205. http://dx.doi.org/10.3329/jasbs.v40i2.46018.

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Nickel nanoparticies (NNPs) were synthesized by reduction of nickel (II) using poiy(vinyl alcohol) (PVA) as a capping agent. The NNPs were characterized by transmission electron microscopy (TEM), scanning electron microscopy (SEM), energy dispersive X-ray (EDX) spectroscopy and X-ray diffraction (XRD) techniques. The addition of PVA has been found to profoundly influence the size, agglomeration and distribution of NNPs. The average diameters of NNPs are in the range of 3-7 nm in presence of PVA. XRD data indicate that NNPs are crystalline with face centered cubic structures. SEM images show the existence of secondary structures such as clusters and loops resulted from interactions between particles. The sizes of the NNPs were by and large uniform due to the use of PVA as the capping agent. FT-IR and thermogravimetric analyses confirm the interaction of PVA w ith NNPs to offer improved thermal stability Asiat. Soc. Bangladesh, Sci. 40(2): 197-205, December 2014

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Vincent, F. H., M. A. Abramowicz, A. A. Zdziarski, M. Wielgus, T. Paumard, G. Perrin, and O. Straub. "Multi-wavelength torus–jet model for Sagittarius A*." Astronomy & Astrophysics 624 (April 2019): A52. http://dx.doi.org/10.1051/0004-6361/201834946.

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Context. The properties of the accretion/ejection flow surrounding the supermassive central black hole of the Galaxy Sgr A* will be scrutinized by the new-generation instrument GRAVITY and the Event Horizon Telescope (EHT). Developing fast, robust, and simple models of such flows is therefore important and very timely. Aims. We want to model the quiescent emission of Sgr A* from radio to mid-infrared wavelengths, using thermal and nonthermal synchrotron. The radiation is emitted by the overlay of a magnetized compact torus close to the black hole, and a large-scale magnetized jet. We compare model spectra and images to the multi-wavelength observable constraints available to date. We simulate EHT observations at 1.3 mm of the best-fit model for different inclinations. methods. We use a simple analytic description for the geometry of the torus and jet. We model their emission by thermal synchrotron and κ-distribution synchrotron, respectively. We use relativistic ray tracing to compute simulated spectra and images, restricting our analysis to the Schwarzschild (zero spin) case. A best-fit is found by adjusting the simulated spectra to the latest observed data, and we check the consistency of our spectral best fits with the radio-image sizes and infrared spectral index constraints. We use the open-source eht-imaging library to generate EHT-reconstructed images. Results. We find perfect spectral fit ( χred2 ≈ 1) both for nearly face-on and nearly edge-on views. These best fits give parameter values very close to those found by the most recent numerical simulations, which are much more complex than our model. The intrinsic radio size of Sgr A* is found to be in reasonable agreement with the centimetric observed constraints. Our best-fit infrared spectral index is in perfect agreement with the latest constraints. Our emission region at 1.3 mm, although larger than the early-EHT Gaussian best fit, does contain bright features at the ≲40 μas scale. EHT-reconstructed images show that torus/jet-specific features persist after the reconstruction procedure, and that these features are sensitive to inclination. Conclusions. The main interest of our model is to provide a simple and fast model of the quiescent state of Sgr A*, which gives extremely similar results to those of state-of-the-art numerical simulations. Our model is easy to use and we publish all the material necessary to reproduce our spectra and images, meaning that anyone interested can use our results relatively straightforwardly. We hope that such a public tool will be useful in the context of the recent and near-future GRAVITY and EHT results.

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Nersesian, A., S. Verstocken, S. Viaene, and M. Baes. "High-resolution radiation transfer modelling of barred galaxies." Proceedings of the International Astronomical Union 15, S341 (November 2019): 65–69. http://dx.doi.org/10.1017/s1743921319002643.

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AbstractDust radiative transfer simulations provide us with the unique opportunity to study the heating mechanisms of dust by the stellar radiation field. From 2D observational images we derive the 3D distributions of stars and dust. Our aim is to analyze the contribution of the different stellar populations to the radiative dust heating processes in the nearby face-on barred galaxies NGC 1365, M 83 and M 95. We wish to decompose the FIR-submm SED and quantify the fraction directly related to star formation. To model the complex geometries mentioned above, we used SKIRT, a state-of-the-art, 3D Monte Carlo radiative transfer code designed to simulate the absorption, scattering and thermal re-emission of dust in a variety of environments. We find that the contribution of the evolved stars (8 Gyr) to the dust heating is non-negligible (∼35%) and can reach as high as 70%. We also find a tight correlation between the heating fraction by the unevolved stars (⩽ 100 Myr) and the specific star formation rate.

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Rahman, MD Abdur, M. Shamim Hossain, Nabil A. Alrajeh, and B. B. Gupta. "A Multimodal, Multimedia Point-of-Care Deep Learning Framework for COVID-19 Diagnosis." ACM Transactions on Multimedia Computing, Communications, and Applications 17, no. 1s (March 31, 2021): 1–24. http://dx.doi.org/10.1145/3421725.

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In this article, we share our experiences in designing and developing a suite of deep neural network–(DNN) based COVID-19 case detection and recognition framework. Existing pathological tests such as RT-PCR-based pathogen RNA detection from nasal swabbing seem to display low detection rates during the early stages of virus contraction. Moreover, the reliance on a few overburdened laboratories based around an epicenter capable of supplying large numbers of RT-PCR tests makes this testing method non-scalable when the rate of infections is high. Similarly, finding an effective drug or vaccine with which to combat COVID-19 requires a long time and many clinical trials. The development of pathological COVID-19 tests is hindered by shortages in the supply chain of chemical reagents necessary for testing on a large scale. This diminishes the speed of diagnosis and the ability to filter out COVID-19 positive patients from uninfected patients on a national level. Existing research has shown that DNN has been successful in identifying COVID-19 from radiological media such as CT scans and X-ray images, audio media such as cough sounds, optical coherence tomography to identify conjunctivitis and pink eye symptoms on the ocular surface, body temperature measurement using smartphone fingerprint sensors or thermal cameras, the use of live facial detection to identify safe social distancing practices from camera images, and face mask detection from camera images. We also investigate the utility of federated learning in diagnosis cases where private data can be trained via edge learning. These point-of-care modalities can be integrated with DNN-based RT-PCR laboratory test results to assimilate multiple modalities of COVID-19 detection and thereby provide more dimensions of diagnosis. Finally, we will present our initial test results, which are encouraging.

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Journal articles on the topic 'Thermal face images'

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