Search results for: Z score facial landmark standardization

Authors: Nouha Khediri, Mohammed Ben Ammar, Monji Kherallah

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Recently, facial emotion recognition (FER) has become increasingly essential to understand the state of the human mind. Accurately classifying emotion from the face is a challenging task. In this paper, we present a facial emotion recognition approach named CV-FER, benefiting from deep learning, especially CNN and VGG16. First, the data is pre-processed with data cleaning and data rotation. Then, we augment the data and proceed to our FER model, which contains five convolutions layers and five pooling layers. Finally, a softmax classifier is used in the output layer to recognize emotions. Based on the above contents, this paper reviews the works of facial emotion recognition based on deep learning. Experiments show that our model outperforms the other methods using the same FER2013 database and yields a recognition rate of 92%. We also put forward some suggestions for future work.

Keywords: CNN, deep-learning, facial emotion recognition, machine learning

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Authors: Choki, Supatchai Boonpratham, Suwannee Luppanapornlarp

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The objective of this study was to find a correlation between cephalometric measurements and visual perception of facial profile in skeletal type II patients. In this study, 250 lateral cephalograms of female patients from age, 20 to 22 years were analyzed. The profile outlines of all the samples were hand traced and transformed into silhouettes by the principal investigator. Profile ratings were done by 9 orthodontists on Visual Analogue Scale from score one to ten (increasing level of convexity). 37 hard issue and soft tissue cephalometric measurements were analyzed by the principal investigator. All the measurements were repeated after 2 weeks interval for error assessment. At last, the rankings of visual perceptions were correlated with cephalometric measurements using Spearman correlation coefficient (P < 0.05). The results show that the increase in facial convexity was correlated with higher values of ANB (A point, nasion and B point), AF-BF (distance from A point to B point in mm), L1-NB (distance from lower incisor to NB line in mm), anterior maxillary alveolar height, posterior maxillary alveolar height, overjet, H angle hard tissue, H angle soft tissue and lower lip to E plane (absolute correlation values from 0.277 to 0.711). In contrast, the increase in facial convexity was correlated with lower values of Pg. to N perpendicular and Pg. to NB (mm) (absolute correlation value -0.302 and -0.294 respectively). From the soft tissue measurements, H angles had a higher correlation with visual perception than facial contour angle, nasolabial angle, and lower lip to E plane. In conclusion, the findings of this study indicated that the correlation of cephalometric measurements with visual perception was less than expected. Only 29% of cephalometric measurements had a significant correlation with visual perception. Therefore, diagnosis based solely on cephalometric analysis can result in failure to meet the patient’s esthetic expectation.

Keywords: cephalometric measurements, facial profile, skeletal type II, visual perception

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Authors: An Guo, Hieyong Jeong, Tianyi Wang, Na Li, Yuko Ohno

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Acupuncture, known as sensory simulation, has been used to treat various disorders for thousands of years. However, present studies had not addressed approaches for noninvasive measurement in order to evaluate therapeutic effect of acupuncture. The purpose of this study is to propose a noninvasive method to evaluate acupuncture by measuring facial temperature through thermal image. Three human subjects were recruited in this study. Each subject received acupuncture therapy for 30 mins. Acupuncture needles (Ø0.16 x 30 mm) were inserted into Baihui point (DU20), Neiguan points (PC6) and Taichong points (LR3), acupuncture needles (Ø0.18 x 39 mm) were inserted into Tanzhong point (RN17), Zusanli points (ST36) and Yinlingquan points (SP9). Facial temperature was recorded by an infrared thermometer. Acupuncture therapeutic effect was compared pre- and post-acupuncture. Experiment results demonstrated that facial temperature changed according to acupuncture therapeutic effect. It was concluded that proposed method showed high potential to evaluate acupuncture by noninvasive measurement of facial temperature.

Keywords: acupuncture, facial temperature, noninvasive evaluation, thermal image

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Authors: L. J. Díaz, M. A. Hernández, A. K. Molina, A. Bermúdez, C. Crane, V. M. Pabón

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One of the most important biological indicators that show the exposure to the radiation is the micronuclei (MN). This technique is using to determinate the radiation effects in blood cultures as a biological control and a complement to the physics dosimetry. In Colombia the necessity to apply this analysis has emerged due to the current biological indicator most used is the chromosomal aberrations (CA), that is why it is essential the MN technique’s standardization and validation to have enough tools to improve the radioprotection topic in the country. Besides, this technique will be applied on the construction of a dose-response curve, that allow measure an approximately dose to irradiated people according to MN frequency found. Inside the steps that carried out to accomplish the standardization and validation is the statistic analysis from the lectures of “in vitro” peripheral blood cultures with different analysts, also it was determinate the best culture medium and conditions for the MN can be detected easily.

Keywords: micronuclei, radioprotection, standardization, validation

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Authors: Jake Tempo, Georgina Williams, Iain Robertson, Claire Pascoe, Darren Rama, Richard Cetti

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Introduction: The twelfth rib is commonly used as a landmark for surgery; however, its variability in length has not been formally studied. The highly variable rib length provides a challenge for urologists seeking a consistent landmark for percutaneous nephrolithotomy and retroperitoneoscopic surgery. Methods and materials: We analysed CT scans of 100 adults who had imaging between 23rd March and twelfth April 2020 at an Australian Hospital. We measured the distance from the mid-sagittal line to the twelfth rib tip in the axial plane as a surrogate for true rib length. We also measured the distance from the twelfth rib tip to the kidney, spleen, and liver. Results: Length from the mid-sagittal line to the right twelfth rib tip varied from 46 (percentile 95%CI 40 to 57) to 136mm (percentile 95%CI 133 to 138). On the left, the distances varied from 55 (percentile 95%CI 50 to 64) to 134mm (percentile 95%CI 131 to 135). Twenty-three percent of people had an organ lying between the tip of the twelfth rib and the kidney on the right, and 11% of people had the same finding on the left. Conclusion: The twelfth rib is highly variable in its length. Similar variability was recorded in the distance from the tip to intra-abdominal organs. Due to the frequency of organs lying between the tip of the rib and the kidney, it should not be used as a landmark for accessing the kidney without prior knowledge of an individual patient’s anatomy, as seen on imaging.

Keywords: PCNL, rib, anatomy, nephrolithotomy

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Authors: Heather Caldwell

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In 1915, state superintendent, Mary C.C. Bradford initiated a state standardization plan in order to improve the quality of schools and the educational experience for all children in Colorado. This plan would change the schools, improving them and offering more opportunities for children, teachers, and the community. In a state where geography limited opportunity to make all schools equal and brought challenges to state school leaders to improve education throughout the state, the leadership prevailed and worked together with local schools and school leaders to make drastic improvements in the curriculum. This paper will discuss this plan and will highlight key contributions to this standardization plan that improved opportunities for all students in the state of Colorado through these educational initiatives.

Keywords: history of education, standardization, curriculum, state superintendent, women in education

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Authors: Ahemd Sameer, Braj Bhushan

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The objective of our study was to compare wayfinding strategies to remember route while navigation in an unfamiliar homogenous environment. Two videos developed using free ware Trimble Sketchup© each having nine identical turns (3 right, 3 left, 3 straight) with no distinguishing feature at any turn. Thirt-two male post-graduate students of IIT Kanpur participated in the study. The experiment was conducted in three phases. In the first phase participant generated a list of personally known items to be used as landmarks. In the second phase participant saw the first video and was required to remember the sequence of turns. In the second video participant was required to imagine a landmark from the list generated in the first phase at each turn and associate the turn with it. In both the task the participant was asked to recall the sequence of turns as it appeared in the video. In the third phase, which was 20 minutes after the second phase, participants again recalled the sequence of turns. Results showed that performance in the first condition i.e. without use of landmarks was better than imaginary landmark condition. The difference, however, became significant when the participant were tested again about 30 minutes later though performance was still better in no-landmark condition. The finding is surprising given the past research in memory and is explained in terms of cognitive factors such as mental workload.

Keywords: Wayfinding, Landmark, Homogenous Environment, Memory

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Authors: Ashutosh Mishra, Nikhil Goyal

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A 3D facial emotion recognition model based on deep learning is proposed in this paper. Two convolution layers and a pooling layer are employed in the deep learning architecture. After the convolution process, the pooling is finished. The probabilities for various classes of human faces are calculated using the sigmoid activation function. To verify the efficiency of deep learning-based systems, a set of faces. The Kaggle dataset is used to verify the accuracy of a deep learning-based face recognition model. The model's accuracy is about 65 percent, which is lower than that of other facial expression recognition techniques. Despite significant gains in representation precision due to the nonlinearity of profound image representations.

Keywords: facial recognition, computational intelligence, convolutional neural network, depth map

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Authors: Amir Feily, Hazhir Shahmoradi Akram, Mojtaba Ghaedi, Farshid Javdani, Naser Hatami, Navid Kalani, Mohammad Zarenezhad

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Background: Filler-induced facial skin ischemia is a potential complication of dermal filler injections that can result in tissue damage and necrosis. Nitroglycerin has been suggested as a treatment option due to its vasodilatory effects, but its efficacy in this context is unclear. Methods: A narrative review was conducted to examine the available evidence on the efficacy of nitroglycerin in filler-induced facial skin ischemia. Relevant studies were identified through a search of electronic databases and manual searching of reference lists. Results: The review found limited evidence supporting the efficacy of nitroglycerin in this context. While there were case reports where the combination of nitroglycerin and hyaluronidase was successful in treating filler-induced facial skin ischemia, there was only one case report where nitroglycerin alone was successful. Furthermore, a rat model did not demonstrate any benefits of nitroglycerin and showed harmful results. Conclusion: The evidence regarding the efficacy of nitroglycerin in filler-induced facial skin ischemia is inconclusive and seems to be against its application. Further research is needed to determine the effectiveness of nitroglycerin alone and in combination with other treatments for this condition. Clinicians should consider limited evidence bases when deciding on treatment options for patients with filler-induced facial skin ischemia.

Keywords: nitroglycerin, facial, skin ischemia, fillers, efficacy, narrative review

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Authors: Daniia Nigmatullina, Vlada Kugurakova, Maxim Talanov

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We present a methodology and our plans of anthropomorphic social agent visualization. That includes creation of three-dimensional model of the virtual companion's head and its facial expressions. Talking Head is a cross-disciplinary project of developing of the human-machine interface with cognitive functions. During the creation of a realistic humanoid robot or a character, there might be the ‘uncanny valley’ problem. We think about this phenomenon and its possible causes. We are going to overcome the ‘uncanny valley’ by increasing of realism. This article discusses issues that should be considered when creating highly realistic characters (particularly the head), their facial expressions and speech visualization.

Keywords: anthropomorphic social agent, facial animation, uncanny valley, visualization, 3D modeling

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Authors: Nigar Sultanova

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Facial morphology is a constant topic of concern for clinicians. When anthropometric methods were introduced into clinical practice to quantify changes in the craniofacial framework, features distinguishing various ethnic group were discovered. Normative data of facial measurements are indispensable to precise determination of the degree of deviations from normal. Establish the reference range of facial proportions in Azerbaijan population by anthropometric measurements of craniofacial complex. The study group consisted of 350 healthy young subjects, 175 males and 175 females, 18 to 25 years of age, from 7 different regions of Azerbaijan. The anthropometric examination was performed according to L.Farkas's method with our modification. In order to determine the morphologic characteristics of seven regions of the craniofacial complex 42 anthropometric measurements were selected. The anthropometric examination. Included the usage of 33 anthropometric landmarks. The 80 indices of the facial proportions, suggested by Farkas and Munro, were calculated: head -10, face - 23, nose - 23, lips - 9, orbits - 11, ears - 4. The date base of the North American white population was used as a reference group. Anthropometric measurements of facial proportions in Azerbaijan population revealed a significant difference between mеn and womеn, according to sexual dimorphism. In comparison with North American whites, considerable differences of facial proportions were observed in the head, face, orbits, labio-oral, nose and ear region. However, in women of the Azerbaijani population, 29 out of 80 proportion indices were similar to the proportions of NAW women. In the men of the Azerbaijani population, 27 out of 80 proportion indices did not reveal a statistically significant difference from the proportions of NAW men. Estimation of the reference range of facial proportions in Azerbaijan population migth be helpful to formulate surgical plan in treatment of congenital or post-traumatic facial deformities successfully.

Keywords: facial morphology, anthropometry, indices of proportion, measurement

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Authors: Faizan Tariq, Moayid Ali Zaidi

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Facial emotion recognition algorithms are expanding rapidly now a day. People are using different algorithms with different combinations to generate best results. There are six basic emotions which are being studied in this area. Author tried to recognize the facial expressions using object detector algorithms instead of traditional algorithms. Two object detection algorithms were chosen which are Faster R-CNN and YOLO. For pre-processing we used image rotation and batch normalization. The dataset I have chosen for the experiments is Static Facial Expression in Wild (SFEW). Our approach worked well but there is still a lot of room to improve it, which will be a future direction.

Keywords: face recognition, emotion recognition, deep learning, CNN

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Authors: Shantanu Vyas, Neerja Meena

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Facial infiltrating lipomatosis is a rare lipomatous lesion, first described by Slavin in 1983. It is a benign pseudotumor pathology. It corresponds to a non-encapsulated collection of mature adipocytes infiltrating the local tissue and hyperplasia of underlying bone leading to a craniofacial deformity. Very few cases have been reported in the literature. We report the case of a 19-year-old female patient, who was consulted for a swelling of the right hemiface progressively evolving since birth. Physical examination revealed facial asymmetry. On palpation, the mass was soft, painless, not compressible, not pulsatile, not fluctuating. In view of the asymptomatic nature and slow progression of the lesion, a lipomatous tumour, namely lipoma, was suggested. CT scan image shows a hyperplastic subcutaneous fat on the right hemiface. On the right jugal and temporal areas, there is a subcutaneous formation of fatty density, poorly limited, with no detectable peripheral capsule. It merges with the adjacent fat. In the bone window, there was a hyperplasia of underlying bone. Facial lipomatosis infiltration of the face is a benign pseudotumor pathology. As a result, it can be confused with other disorders, in particular, hemifacial hyperplasia. Combination of physical and radiological findings can establish the diagnosis. Surgical treatment is done for cosmetic purposes.

Keywords: cosmetic correction and facial assemetry, aesthetic results, facial infiltration, surgery

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Authors: Ekin Ozer, Maria Q. Feng, Rupa Purasinghe

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Structural deterioration of bridge systems possesses an ongoing threat to the transportation networks. Besides, landmark bridges’ integrity and safety are more than sole functionality, since they provide a strong presence for the society and nations. Therefore, an innovative and sustainable method to inspect landmark bridges is essential to ensure their resiliency in the long run. In this paper, a recently introduced concept, smartphone-based modal frequency estimation is addressed, and this paper targets to authenticate the fidelity of smartphone-based vibration measurements gathered from three landmark suspension bridges. Firstly, smartphones located at the bridge mid-span are adopted as portable and standalone vibration measurement devices. Then, their embedded accelerometers are utilized to gather vibration response under operational loads, and eventually frequency domain characteristics are deduced. The preliminary analysis results are compared with the reference publications and high-quality monitoring data to validate the usability of smartphones on long-span landmark suspension bridges. If the technical challenges such as high period of vibration, low amplitude excitation, embedded smartphone sensor features, sampling, and citizen engagement are tackled, smartphones can provide a novel and cost-free crowdsourcing tool for maintenance of these landmark structures. This study presents the early phase findings from three signature structures located in the United States.

Keywords: smart and mobile sensing, structural health monitoring, suspension bridges, vibration analysis

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Authors: S. Kherchaoui, A. Houacine

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This paper presents a facial expression recognition system. It performs identification and classification of the seven basic expressions; happy, surprise, fear, disgust, sadness, anger, and neutral states. It consists of three main parts. The first one is the detection of a face and the corresponding facial features to extract the most expressive portion of the face, followed by a normalization of the region of interest. Then calculus of curvelet coefficients is performed with dimensionality reduction through principal component analysis. The resulting coefficients are combined with two ratios; mouth ratio and face edge ratio to constitute the whole feature vector. The third step is the classification of the emotional state using the SVM method in the feature space.

Keywords: facial expression identification, curvelet coefficient, support vector machine (SVM), recognition system

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Authors: Erick C. Valverde, Wansu Lim

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Facial emotion recognition (FER) system has been recently developed for more advanced computer vision applications. The ability to identify human emotions would enable smart healthcare facility to diagnose mental health illnesses (e.g., depression and stress) as well as better human social interactions with smart technologies. The FER system involves two steps: 1) face detection task and 2) facial emotion recognition task. It classifies the human expression in various categories such as angry, disgust, fear, happy, sad, surprise, and neutral. This system requires intensive research to address issues with human diversity, various unique human expressions, and variety of human facial features due to age differences. These issues generally affect the ability of the FER system to detect human emotions with high accuracy. Early stage of FER systems used simple supervised classification task algorithms like K-nearest neighbors (KNN) and artificial neural networks (ANN). These conventional FER systems have issues with low accuracy due to its inefficiency to extract significant features of several human emotions. To increase the accuracy of FER systems, deep learning (DL)-based methods, like convolutional neural networks (CNN), are proposed. These methods can find more complex features in the human face by means of the deeper connections within its architectures. However, the inference speed and computational costs of a DL-based FER system is often disregarded in exchange for higher accuracy results. To cope with this drawback, an optimized DL-based FER system is proposed in this study.An extreme version of Inception V3, known as Xception model, is leveraged by applying different network optimization methods. Specifically, network pruning and quantization are used to enable lower computational costs and reduce memory usage, respectively. To support low resource requirements, a 68-landmark face detector from Dlib is used in the early step of the FER system.Furthermore, a DL compiler is utilized to incorporate advanced optimization techniques to the Xception model to improve the inference speed of the FER system. In comparison to VGG-Net and ResNet50, the proposed optimized DL-based FER system experimentally demonstrates the objectives of the network optimization methods used. As a result, the proposed approach can be used to create an efficient and real-time FER system.

Keywords: deep learning, face detection, facial emotion recognition, network optimization methods

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Authors: Sana Ilyas, Kishalaya Mukherjee, Suresh Shetty

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Lip Augmentation has become more common in recent years. Patients do not expect to experience facial palsy after having lip augmentation. This poster will present the findings of such a presentation and will discuss the possible pathophysiology and management. (This poster has been published as a paper in the dental update, June 2022) Aim: The aim of the study was to explore the link between facial nerve palsy and lip fillers, to explore the literature surrounding facial nerve palsy, and to discuss the case of a patient who presented with facial nerve palsy with seemingly unknown cause. Methodology: There was a thorough assessment of the current literature surrounding the topic. This included published papers in journals through PubMed database searches and printed books on the topic. A case presentation was discussed in detail of a patient presenting with peripheral facial nerve palsy and associating it with lip augmentation that she had a day prior. Results and Conclusion: Even though the pathophysiology may not be clear for this presentation, it is important to highlight uncommon presentations or complications that may occur after treatment. This can help with understanding and managing similar cases, should they arise.It is also important to differentiate cause and association in order to make an accurate diagnosis. This may be difficult if there is little scientific literature. Therefore, further research can help to improve the understanding of the pathophysiology of similar presentations. This poster has been published as a paper in dental update, June 2022, and therefore shares a similar conclusiom.

Keywords: facial palsy, lip augmentation, causation and correlation, dental cosmetics

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Authors: Bing Gu

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Abstract—Most of Conventional facial recognition systems are based on image features, such as LBP, SIFT. Recently some DBN-based 2D facial recognition systems have been proposed. However, we find there are few DBN-based 3D facial recognition system and relative researches. 3D facial images include all the individual biometric information. We can use these information to build more accurate features, So we present our DBN-based face recognition system using Light Field. We can see Light Field as another presentation of 3D image, and Light Field Camera show us a way to receive a Light Field. We use the commercially available Light Field Camera to act as the collector of our face recognition system, and the system receive a state-of-art performance as convenient as conventional 2D face recognition system.

Keywords: DBN, face recognition, light field, Lytro

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Authors: Jemma Porrett

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Background: We present a literature review examining the research surrounding tick paralysis resulting in facial nerve palsy. A case of an intra-aural paralysis tick bite resulting in unilateral facial nerve palsy is also discussed. Methods: A novel case of otoacariasis with associated ipsilateral facial nerve involvement is presented. Additionally, we conducted a review of the literature, and we searched the MEDLINE and EMBASE databases for relevant literature published between 1915 and 2020. Utilising the following keywords; 'Ixodes', 'Facial paralysis', 'Tick bite', and 'Australia', 18 articles were deemed relevant to this study. Results: Eighteen articles included in the review comprised a total of 48 patients. Patients' ages ranged from one year to 84 years of age. Ten studies estimated the possible duration between a tick bite and facial nerve palsy, averaging 8.9 days. Forty-one patients presented with a single tick within the external auditory canal, three had a single tick located on the temple or forehead region, three had post-auricular ticks, and one patient had a remarkable 44 ticks removed from the face, scalp, neck, back, and limbs. A complete ipsilateral facial nerve palsy was present in 45 patients, notably, in 16 patients, this occurred following tick removal. House-Brackmann classification was utilised in 7 patients; four patients with grade 4, one patient with grade three, and two patients with grade 2 facial nerve palsy. Thirty-eight patients had complete recovery of facial palsy. Thirteen studies were analysed for time to recovery, with an average time of 19 days. Six patients had partial recovery at the time of follow-up. One article reported improvement in facial nerve palsy at 24 hours, but no further follow-up was reported. One patient was lost to follow up, and one article failed to mention any resolution of facial nerve palsy. One patient died from respiratory arrest following generalized paralysis. Conclusions: Tick paralysis is a severe but preventable disease. Careful examination of the face, scalp, and external auditory canal should be conducted in patients presenting with otalgia and facial nerve palsy, particularly in tropical areas, to exclude the possibility of tick infestation.

Keywords: facial nerve palsy, tick bite, intra-aural, Australia

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Authors: Kyung-Ja Cho, Sun Jin Park

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This study examined what effective dimension affects facial attractiveness. Two orthogonal dimensions, sharp-soft and babyish-mature, were used to rate the levels of facial attractiveness in 20’s women. This research also investigated the sex difference on the effect of effective dimension of face on attractiveness. The test subjects composed of 15 males and 18 females. They looked 330 photos of women in 20s. Then they rated the levels of the effective dimensions of faces with sharp-soft and babyish-mature, and the attraction with charmless-charming. The respond forms were Likert scales, the answer was scored from 1 to 9. As a result of multiple regression analysis, the subject reported the milder and younger appearance as more attractive. Both male and female subjects showed the same evaluation. This result means that two effective dimensions have the effect on estimating attractiveness.

Keywords: affective dimension of faces, facial attractiveness, sharp-soft, babyish-mature

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Authors: Andreas Aceranti, Simonetta Vernocchi, Marco Colorato, Daniel Zaccariello

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Our study explores the usefulness of implementing facial expression recognition capabilities and using the Facial Action Coding System (FACS) in contexts where the other person is wearing a mask. In the communication process, the subjects use a plurality of distinct and autonomous reporting systems. Among them, the system of mimicking facial movements is worthy of attention. Basic emotion theorists have identified the existence of specific and universal patterns of facial expressions related to seven basic emotions -anger, disgust, contempt, fear, sadness, surprise, and happiness- that would distinguish one emotion from another. However, due to the COVID-19 pandemic, we have come up against the problem of having the lower half of the face covered and, therefore, not investigable due to the masks. Facial-emotional behavior is a good starting point for understanding: (1) the affective state (such as emotions), (2) cognitive activity (perplexity, concentration, boredom), (3) temperament and personality traits (hostility, sociability, shyness), (4) psychopathology (such as diagnostic information relevant to depression, mania, schizophrenia, and less severe disorders), (5) psychopathological processes that occur during social interactions patient and analyst. There are numerous methods to measure facial movements resulting from the action of muscles, see for example, the measurement of visible facial actions using coding systems (non-intrusive systems that require the presence of an observer who encodes and categorizes behaviors) and the measurement of electrical "discharges" of contracting muscles (facial electromyography; EMG). However, the measuring system invented by Ekman and Friesen (2002) - "Facial Action Coding System - FACS" is the most comprehensive, complete, and versatile. Our study, carried out on about 1,500 subjects over three years of work, allowed us to highlight how the movements of the hands and upper part of the face change depending on whether the subject wears a mask or not. We have been able to identify specific alterations to the subjects’ hand movement patterns and their upper face expressions while wearing masks compared to when not wearing them. We believe that finding correlations between how body language changes when our facial expressions are impaired can provide a better understanding of the link between the face and body non-verbal language.

Keywords: facial action coding system, COVID-19, masks, facial analysis

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Authors: Swati Srivastava, Ashish Kumar Upadhyay

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Using longitudinal data from three waves of Young Lives Study and Ordinary Least Square methods, study has investigated the effect of birth order and arrival of younger siblings on child development in India. Study used child’s height for age z-score, weight for age z-score, BMI for age z-score, Peabody Picture Vocabulary Test (PPVT-Score)c, maths score, Early Grade Reading Assessment Test (ERGA) score, and memory score to measure the physical and cognitive development of child during wave-3. Findings suggest that having a high birth order is detrimental for child development and the gap between adjacent siblings is larger for children late in the birth sequences than early in the birth sequences. Study also reported that not only older siblings but arrival of younger siblings before assessment of test also reduces the development of a child. The effects become stronger in case of female children than male children.

Keywords: height for age z-score, weight for age z-score, BMI for z-score, PPVT score, math score, EGRA score, memory score, birth order, siblings, Young Lives Study, India

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Authors: Huixin Wei, Shibin Wang, Linan Li, Lei Zhou, Xinhao Tu

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Facial skin is a biomedical material with complex mechanical properties of anisotropy, viscoelasticity, and hyperelasticity. The mechanical properties of facial skin are crucial for a number of applications including facial plastic surgery, animation, dermatology, cosmetic industry, and impact biomechanics. Skin is a complex multi-layered material which can be broadly divided into three main layers, the epidermis, the dermis, and the hypodermis. Collagen fibers account for 75% of the dry weight of dermal tissue, and it is these fibers which are responsible for the mechanical properties of skin. Many research on the anisotropic mechanical properties are mainly concentrated on in vitro, but there is a great difference between in vivo and in vitro for mechanical properties of the skin. In this study, we presented a method to measure the mechanical properties of facial skin in vivo. Digital image correlation (DIC) and indentation tests were used to obtain the experiment data, including the deformation of facial surface and indentation force-displacement curve. Then, the experiment was simulated using a finite element (FE) model. Application of Computed Tomography (CT) and reconstruction techniques obtained the real tissue geometry. A three-dimensional FE model of facial skin, including a bi-layer system, was obtained. As the epidermis is relatively thin, the epidermis and dermis were regarded as one layer and below it was hypodermis in this study. The upper layer was modeled as a Gasser-Ogden-Holzapfel (GOH) model to describe hyperelastic and anisotropic behaviors of the dermis. The under layer was modeled as a linear elastic model. In conclusion, the material properties of two-layer were determined by minimizing the error between the FE data and experimental data.

Keywords: facial skin, indentation test, finite element, digital image correlation, computed tomography

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Authors: Hoyeon Park, Kyoung-jae Kim

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The product recommendation is a field of research that has received much attention in the recent information overload phenomenon. The proliferation of the mobile environment and social media cannot help but affect the results of the recommendation depending on how the factors of the user's situation are reflected in the recommendation process. Recently, research has been spreading attention to the context-aware recommender system which is to reflect user's contextual information in the recommendation process. However, until now, most of the context-aware recommender system researches have been limited in that they reflect the passive context of users. It is expected that the user will be able to express his/her contextual information through his/her active behavior and the importance of the context-aware recommender system reflecting this information can be increased. The purpose of this study is to propose a context-aware recommender system that can reflect the user's emotional state as an active context information to recommendation process. The context-aware recommender system is a recommender system that can make more sophisticated recommendations by utilizing the user's contextual information and has an advantage that the user's emotional factor can be considered as compared with the existing recommender systems. In this study, we propose a method to infer the user's emotional state, which is one of the user's context information, by using the user's facial expression data and to reflect it on the recommendation process. This study collects the facial expression data of a user who is looking at a specific product and the user's product preference score. Then, we classify the facial expression data into several categories according to the previous research and construct a model that can predict them. Next, the predicted results are applied to existing collaborative filtering with contextual information. As a result of the study, it was shown that the recommended results of the context-aware recommender system including facial expression information show improved results in terms of recommendation performance. Based on the results of this study, it is expected that future research will be conducted on recommender system reflecting various contextual information.

Keywords: context-aware, emotional state, recommender systems, business analytics

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Authors: Muhammad Maisam Abbas, Salman Tariq, Usama Riaz, Muhammad Tanveer, Humaira Abdul Ghafoor

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Autism Spectrum Disorder (ASD) refers to a developmental disorder that impairs an individual's communication and interaction ability. Individuals feel difficult to read facial expressions while communicating or interacting. Facial Expression Recognition (FER) is a unique method of classifying basic human expressions, i.e., happiness, fear, surprise, sadness, disgust, neutral, and anger through static and dynamic sources. This paper conducts a comprehensive comparison and proposed optimal method for a continued research project—a system that can assist people who have Autism Spectrum Disorder (ASD) in recognizing facial expressions. Comparison has been conducted on three supervised learning algorithms EigenFace, FisherFace, and LBPH. The JAFFE, CK+, and TFEID (I&II) datasets have been used to train and test the algorithms. The results were then evaluated based on variance, standard deviation, and accuracy. The experiments showed that FisherFace has the highest accuracy for all datasets and is considered the best algorithm to be implemented in our system.

Keywords: autism spectrum disorder, ASD, EigenFace, facial expression recognition, FisherFace, local binary pattern histogram, LBPH

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Authors: Chaudhary Muhammad Aqdus Ilyas, Matthias Rehm, Kamal Nasrollahi, Thomas B. Moeslund

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This paper presents the investigation of data collection procedures, associated with robots when placed with traumatic brain injured (TBI) patients for rehabilitation purposes through facial expression and mood analysis. Rehabilitation after TBI is very crucial due to nature of injury and variation in recovery time. It is advantageous to analyze these emotional signals in a contactless manner, due to the non-supportive behavior of patients, limited muscle movements and increase in negative emotional expressions. This work aims at the development of framework where robots can recognize TBI emotions through facial expressions to perform rehabilitation tasks by physical, cognitive or interactive activities. The result of these studies shows that with customized data collection strategies, proposed framework identify facial and emotional expressions more accurately that can be utilized in enhancing recovery treatment and social interaction in robotic context.

Keywords: computer vision, convolution neural network- long short term memory network (CNN-LSTM), facial expression and mood recognition, multimodal (RGB-thermal) analysis, rehabilitation, robots, traumatic brain injured patients

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Authors: Mohammadamin Abbasnejad

Abstract:

The analysis of expression and facial Action Units (AUs) detection are very important tasks in fields of computer vision and Human Computer Interaction (HCI) due to the wide range of applications in human life. Many works have been done during the past few years which has their own advantages and disadvantages. In this work, we present a new model based on Gaussian Conditional Random Field. We solve our objective problem using ADMM and we show how well the proposed model works. We train and test our work on two facial expression datasets, CK+, and RU-FACS. Experimental evaluation shows that our proposed approach outperform state of the art expression recognition.

Keywords: Gaussian Conditional Random Field, ADMM, convergence, gradient descent

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Authors: Hao Shen, Aparna Labroo

Abstract:

Across four studies, we show people in a negative mood avoid anticipated enjoyable experiences because of the subjective difficulty in simulating those experiences, and they misattribute these feelings of difficulty to reduced pleasantness of the anticipated experience. We observe the avoidance of enjoyable experiences only for anticipated experiences that involve smile-like facial-muscular simulation. When the need for facial-muscular simulation is attenuated, or when the anticipated experience relies on facial-muscular simulation to a lesser extent, people in a negative mood no longer avoid enjoyable experiences, but rather seek such experiences because they fit better with their ongoing mood-repair goals.

Keywords: emotion regulation, mood repair, embodiment, anticipated experiences

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Authors: Imme Petersen, Wiebke Sick, Regine Kollek

Abstract:

In systems medicine, high-throughput technologies produce large amounts of data on different biological and pathological processes, including (disturbed) gene expressions, metabolic pathways and signaling. The large volume of data of different types, stored in separate databases and often located at different geographical sites have posed new challenges regarding data handling and processing. Tools based on bioinformatics have been developed to resolve the upcoming problems of systematizing, standardizing and integrating the various data. However, the heterogeneity of data gathered at different levels of biological complexity is still a major challenge in data analysis. To build multilayer disease modules, large and heterogeneous data of disease-related information (e.g., genotype, phenotype, environmental factors) are correlated. Therefore, a great deal of attention in systems medicine has been put on data standardization, primarily to retrieve and combine large, heterogeneous datasets into standardized and incorporated forms and structures. However, this data-centred concept of standardization in systems medicine is contrary to the debate in science and technology studies (STS) on standardization that rather emphasizes the dynamics, contexts and negotiations of standard operating procedures. Based on empirical work on research consortia that explore the molecular profile of diseases to establish systems medical approaches in the clinic in Germany, we trace how standardized data are processed and shaped by bioinformatics tools, how scientists using such data in research perceive such standard operating procedures and which consequences for knowledge production (e.g. modeling) arise from it. Hence, different concepts and meanings of standardization are explored to get a deeper insight into standard operating procedures not only in systems medicine, but also beyond.

Keywords: data, science and technology studies (STS), standardization, systems medicine

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Authors: Xiaoqi Jia, Qing Zhu, Hao Zhang, Su Yang

Abstract:

A gender recognition system is able to tell the gender of the given person through a few of frontal facial images. An effective gender recognition approach enables to improve the performance of many other applications, including security monitoring, human-computer interaction, image or video retrieval and so on. In this paper, we present an effective method for gender classification task in frontal facial images based on deep belief networks (DBNs), which can pre-train model and improve accuracy a little bit. Our experiments have shown that the pre-training method with DBNs for gender classification task is feasible and achieves a little improvement of accuracy on FERET and CAS-PEAL-R1 facial datasets.

Keywords: gender recognition, beep belief net-works, semi-supervised learning, greedy-layer wise RBMs

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