scholarly journals Analysis of Facial Information for Healthcare Applications: A Survey on Computer Vision-Based Approaches

Information ◽  
2020 ◽  
Vol 11 (3) ◽  
pp. 128 ◽  
Author(s):  
Marco Leo ◽  
Pierluigi Carcagnì ◽  
Pier Luigi Mazzeo ◽  
Paolo Spagnolo ◽  
Dario Cazzato ◽  
...  
Keyword(s):  
Computer Vision ◽  
Facial Feature ◽  
Cutting Edge ◽  
Healthcare Applications ◽  
Face Analysis ◽  
Facial Information ◽  
The Face ◽  
Local Cues

This paper gives an overview of the cutting-edge approaches that perform facial cue analysis in the healthcare area. The document is not limited to global face analysis but it also concentrates on methods related to local cues (e.g., the eyes). A research taxonomy is introduced by dividing the face in its main features: eyes, mouth, muscles, skin, and shape. For each facial feature, the computer vision-based tasks aiming at analyzing it and the related healthcare goals that could be pursued are detailed.

scholarly journals Convolutional Neural Networks for Semantic Segmentation as a Tool for Multiclass Face Analysis in Thermal Infrared

2021 ◽  
Vol 40 (1) ◽  
Author(s):  
David Müller ◽  
Andreas Ehlen ◽  
Bernd Valeske
Keyword(s):  
Neural Networks ◽  
Convolutional Neural Networks ◽  
Semantic Segmentation ◽  
Thermal Infrared ◽  
Relative Temperature ◽  
Face Analysis ◽  
Image Translation ◽  
The Face ◽  
Live Image ◽  
Quantitative Thermography

AbstractConvolutional neural networks were used for multiclass segmentation in thermal infrared face analysis. The principle is based on existing image-to-image translation approaches, where each pixel in an image is assigned to a class label. We show that established networks architectures can be trained for the task of multiclass face analysis in thermal infrared. Created class annotations consisted of pixel-accurate locations of different face classes. Subsequently, the trained network can segment an acquired unknown infrared face image into the defined classes. Furthermore, face classification in live image acquisition is shown, in order to be able to display the relative temperature in real-time from the learned areas. This allows a pixel-accurate temperature face analysis e.g. for infection detection like Covid-19. At the same time our approach offers the advantage of concentrating on the relevant areas of the face. Areas of the face irrelevant for the relative temperature calculation or accessories such as glasses, masks and jewelry are not considered. A custom database was created to train the network. The results were quantitatively evaluated with the intersection over union (IoU) metric. The methodology shown can be transferred to similar problems for more quantitative thermography tasks like in materials characterization or quality control in production.

scholarly journals Facial Feature Model for a Portrait Video Stylization

Symmetry ◽  
2018 ◽  
Vol 10 (10) ◽  
pp. 442 ◽  
Author(s):  
Dongxue Liang ◽  
Kyoungju Park ◽  
Przemyslaw Krompiec
Keyword(s):  
Facial Feature ◽  
Feature Model ◽  
Facial Features ◽  
Outer Face ◽  
Flow Estimation ◽  
Photorealistic Rendering ◽  
Stroke Models ◽  
The Face ◽  
Face Contour ◽  
Human Faces

With the advent of the deep learning method, portrait video stylization has become more popular. In this paper, we present a robust method for automatically stylizing portrait videos that contain small human faces. By extending the Mask Regions with Convolutional Neural Network features (R-CNN) with a CNN branch which detects the contour landmarks of the face, we divided the input frame into three regions: the region of facial features, the region of the inner face surrounded by 36 face contour landmarks, and the region of the outer face. Besides keeping the facial features region as it is, we used two different stroke models to render the other two regions. During the non-photorealistic rendering (NPR) of the animation video, we combined the deformable strokes and optical flow estimation between adjacent frames to follow the underlying motion coherently. The experimental results demonstrated that our method could not only effectively reserve the small and distinct facial features, but also follow the underlying motion coherently.

scholarly journals Web Application for Emotion-based Music Player

2021 ◽  
Vol 9 (12) ◽  
pp. 11-14
Author(s):  
Kamal Naina Soni
Keyword(s):  
Computer Vision ◽  
Human Brain ◽  
Facial Expressions ◽  
Web Application ◽  
Emotional State ◽  
Current State ◽  
The Face ◽  
Current Mood ◽  
The Individual ◽  
Music Player

Abstract: Human expressions play an important role in the extraction of an individual's emotional state. It helps in determining the current state and mood of an individual, extracting and understanding the emotion that an individual has based on various features of the face such as eyes, cheeks, forehead, or even through the curve of the smile. A survey confirmed that people use Music as a form of expression. They often relate to a particular piece of music according to their emotions. Considering these aspects of how music impacts a part of the human brain and body, our project will deal with extracting the user’s facial expressions and features to determine the current mood of the user. Once the emotion is detected, a playlist of songs suitable to the mood of the user will be presented to the user. This can be a big help to alleviate the mood or simply calm the individual and can also get quicker song according to the mood, saving time from looking up different songs and parallel developing a software that can be used anywhere with the help of providing the functionality of playing music according to the emotion detected. Keywords: Music, Emotion recognition, Categorization, Recommendations, Computer vision, Camera

Design and Evaluation of Vision-Based Head and Face Tracking Interfaces for Assistive Input

2014 ◽  
pp. 180-205 ◽  
Author(s):  
Chamin Morikawa ◽  
Michael J. Lyons
Keyword(s):  
Human Computer Interaction ◽  
Qualitative Evaluation ◽  
Facial Feature ◽  
Face Tracking ◽  
Input Devices ◽  
Interaction Styles ◽  
Facial Feature Tracking ◽  
The Face ◽  
Gesture Interfaces ◽  
Computer Interaction

Interaction methods based on computer-vision hold the potential to become the next powerful technology to support breakthroughs in the field of human-computer interaction. Non-invasive vision-based techniques permit unconventional interaction methods to be considered, including use of movements of the face and head for intentional gestural control of computer systems. Facial gesture interfaces open new possibilities for assistive input technologies. This chapter gives an overview of research aimed at developing vision-based head and face-tracking interfaces. This work has important implications for future assistive input devices. To illustrate this concretely the authors describe work from their own research in which they developed two vision-based facial feature tracking algorithms for human computer interaction and assistive input. Evaluation forms a critical component of this research and the authors provide examples of new quantitative evaluation tasks as well as the use of model real-world applications for the qualitative evaluation of new interaction styles.

An Overview of Telemedicine Technologies for Healthcare Applications

2018 ◽  
pp. 732-759 ◽  
Author(s):  
P. S. Pandian
Keyword(s):  
Health Care ◽  
Health Professionals ◽  
Physiological Monitoring ◽  
Improve Quality ◽  
Healthcare Applications ◽  
Allied Health Professionals ◽  
Face To Face ◽  
Communications Technologies ◽  
The Face

Medical care generally relies on the face-to-face encounter between patients and doctors. In places where face-to-face encounters are not possible, telemedicine technologies are relied upon to link patients to specialist doctors for consultation and to obtain opinion. The telemedicine technologies provide improved health care to the underprivileged in inaccessible areas at reduced cost. Telemedicine also improve quality of health care and more importantly reduce the isolation of specialists, nurses and allied health professionals. This review papers discusses the telemedicine technologies and its history, the communications technologies that are being used. The paper also covers the advantages and benefits of telemedicine. Also the recent advances that are going on in telemedicine in the areas of m-health, Wearable Physiological Monitoring System (WPMS), Wireless Body Area Networks (WBAN). Finally, the paper concludes with some of the drawbacks or issues of telemedicine technologies.

A new dimension for deployment

2019 ◽  
Vol 35 (6) ◽  
pp. 21-23
Keyword(s):  
Case Studies ◽  
Design Methodology ◽  
Reading Time ◽  
Cutting Edge ◽  
Content Type ◽  
Commercial Use ◽  
Course Of Action ◽  
The Face ◽  
Pertinent Information ◽  
Practical Implications

Purpose This paper aims to review the latest management developments across the globe and pinpoints the practical implications from cutting-edge research and case studies. Design/methodology/approach This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context. Findings There is often a disconnect between science and business that is hard to fathom. Sometimes, of course, it is easy to see why two parties can seem so far apart – the scientist in search of truth and uninterested in any practical or commercial use of an invention – the industrialist who is dedicated to one course of action and unwilling to learn from research, which can prove it is the wrong one. Both people are as guilty as each other of missing what is staring them in the face. And yet, this dogged pursuit of a single goal is what represents them and perhaps enables them to more successful than other at what they choose to do. Originality/value The briefing saves busy executives and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy-to-digest format.

Differential Characteristics of Face Neuron Responses Within the Anterior Superior Temporal Sulcus of Macaques

2005 ◽  
Vol 94 (2) ◽  
pp. 1252-1266 ◽  
Author(s):  
Wania C. De Souza ◽  
Satoshi Eifuku ◽  
Ryoi Tamura ◽  
Hisao Nishijo ◽  
Taketoshi Ono
Keyword(s):  
Spatial Relationship ◽  
Superior Temporal Sulcus ◽  
Hierarchical Organization ◽  
Gaze Direction ◽  
Functional Heterogeneity ◽  
Oblique View ◽  
Macaque Monkeys ◽  
Facial Information ◽  
The Face ◽  
Rostral Region

The anterior superior temporal sulcus (STS) of macaque monkeys is thought to be involved in the analysis of incoming perceptual information for face recognition or identification; face neurons in the anterior STS show tuning to facial views and/or gaze direction in the faces of others. Although it is well known that both the anatomical architecture and the connectivity differ between the rostral and caudal regions of the anterior STS, the functional heterogeneity of these regions is not well understood. We recorded the activity of face neurons in the anterior STS of macaque monkeys during the performance of a face identification task, and we compared the characteristics of face neuron responses in the caudal and rostral regions of the anterior STS. In the caudal region, facial views that elicited optimal responses were distributed among all views tested; the majority of face neurons responded symmetrically to right and left views. In contrast, the face neurons in the rostral region responded optimally to a single oblique view; right-left symmetry among the responses of these neurons was less evident. Modulation of the face neuron responses according to gaze direction was more evident in the rostral region. Some of the face neuron responses were specific to a certain combination of a particular facial view and a particular gaze direction, whereas others were associated with the relative spatial relationship between facial view and gaze direction. Taken together, these results indicated the existence of a functional heterogeneity within the anterior STS and suggested a plausible hierarchical organization of facial information processing.

scholarly journals Does Prosopagnosia Take the Eyes Out of Face Representations? Evidence for a Defect in Representing Diagnostic Facial Information following Brain Damage

2005 ◽  
Vol 17 (10) ◽  
pp. 1652-1666 ◽  
Author(s):  
Roberto Caldara ◽  
Philippe Schyns ◽  
Eugéne Mayer ◽  
Marie L. Smith ◽  
Frédéric Gosselin ◽  
...  
Keyword(s):  
Brain Damage ◽  
Face Processing ◽  
Processing System ◽  
Facial Information ◽  
Spatial Frequencies ◽  
The Face ◽  
Occipitotemporal Cortex ◽  
Response Classification ◽  
Unfamiliar Faces ◽  
Normal Controls

One of the most impressive disorders following brain damage to the ventral occipitotemporal cortex is prosopagnosia, or the inability to recognize faces. Although acquired prosopagnosia with preserved general visual and memory functions is rare, several cases have been described in the neuropsychological literature and studied at the functional and neural level over the last decades. Here we tested a brain-damaged patient (PS) presenting a deficit restricted to the category of faces to clarify the nature of the missing and preserved components of the face processing system when it is selectively damaged. Following learning to identify 10 neutral and happy faces through extensive training, we investigated patient PS's recognition of faces using Bubbles, a response classification technique that sampled facial information across the faces in different bandwidths of spatial frequencies [Gosselin, F., & Schyns, P. E., Bubbles: A technique to reveal the use of information in recognition tasks. Vision Research, 41, 2261-2271, 2001]. Although PS gradually used less information (i.e., the number of bubbles) to identify faces over testing, the total information required was much larger than for normal controls and decreased less steeply with practice. Most importantly, the facial information used to identify individual faces differed between PS and controls. Specifically, in marked contrast to controls, PS did not use the optimal eye information to identify familiar faces, but instead the lower part of the face, including the mouth and the external contours, as normal observers typically do when processing unfamiliar faces. Together, the findings reported here suggest that damage to the face processing system is characterized by an inability to use the information that is optimal to judge identity, focusing instead on suboptimal information.

Application of Gabor Dictionary and SL0 Norm in Disguise Face Recognition

2013 ◽  
Vol 278-280 ◽  
pp. 1211-1214
Author(s):  
Jun Ying Zeng ◽  
Jun Ying Gan ◽  
Yi Kui Zhai
Keyword(s):  
Face Recognition ◽  
Function Approximation ◽  
Multiple Scales ◽  
Recognition Rate ◽  
Principal Component ◽  
Facial Feature ◽  
Training Image ◽  
Recognition Algorithm ◽  
The Face ◽  
Gabor Dictionary

A fast sparse representation face recognition algorithm based on Gabor dictionary and SL0 norm is proposed in this paper. The Gabor filters, which could effectively extract local directional features of the image at multiple scales, are less sensitive to variations of illumination, expression and camouflage. SL0 algorithm, with the advantages of calculation speed，require fewer measurement values by continuously differentiable function approximation L0 norm and reconstructed sparse signal by minimizing the approximate L0 norm. The algorithm obtain the local feature face by extracting the Gabor face feature, reduce the dimensions by principal component analysis, fast sparse classify by the SL0 norm. Under camouflage condition, The algorithm block the Gabor facial feature and improve the speed of formation of the Gabor dictionary. The experimental results on AR face database show that the proposed algorithm can improve recognition speed and recognition rate to some extent and can generalize well to the face recognition, even with a few training image per class.

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