Search results for: facial action

Authors: Saw Thiha, Jay Rajasekera

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A boom in video conferencing generated millions of hours of video data daily to be analyzed. However, such enormous data pose certain scalability issues to be analyzed efficiently, let alone do it in real-time, as online conferences can involve hundreds of people and can last for hours. This paper proposes an efficient online proctoring solution that can analyze the online conferences real-time on edge devices such as Android, iOS, and desktops. Since the computation can be done upfront on the devices where online conferences take place, it can scale well without requiring intensive resources such as GPU servers and complex cloud infrastructure. According to the linear models, face orientation does indeed impact the perceived eye openness. Also, the proposed z score facial landmark standardization was proven to be functional in detecting face orientation and contributed to classifying eye blinks with single eyelid distance computation while achieving a better f1 score and accuracy than the Eye Aspect Ratio (EAR) threshold method. Last but not least, the authors implemented the solution natively in the MediaPipe framework and open-sourced it along with the reproducible experimental results on GitHub. The solution provides face orientation, eye blink, facial activity, and translation detections out of the box and is highly customizable and extensible.

Keywords: android, desktop, edge computing, blink, face orientation, facial activity and translation, MediaPipe, open source, real-time, video conference, web, iOS, Z score facial landmark standardization

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Authors: Noha El Toukhy

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The ‘beauty is good” stereotype suggests that people perceive attractive people as having several positive characteristics. Likewise, an “anomalous-is-bad” stereotype is hypothesized to facilitate biases against people with anomalous or less attractive faces. Researchers integrated both into a stereotype content model, which is one of the frameworks used in this study to assess how facial anomalies influence people’s social attitudes and, specifically, people’s ratings of warmth and competence. The mind perception theory, as well as the assessment of animalistic and mechanistic dehumanization against facially anomalous people, are two further frameworks that we are using in this study. This study will test the hypothesis that people have negative attitudes towards people with facial anomalies. We also hypothesize that people have negative biases toward faces with visible differences compared to faces without such differences regardless of the specific type of anomaly, as well as that individual differences in psychological dispositions bear on the expression of the anomalous-is-bad stereotype. Using highly controlled and some never-before-used face stimuli, this pre-registered study examines whether moral character influences perceptions of attractiveness, warmth, and competence for facial anomalies.

Keywords: adolescents, attractiveness, competence, social attitudes, warmth

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Authors: Kriddikorn Kaewwongsri, Nikom Suvonvorn

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In the deep south of Thailand, checkpoints for people verification are necessary for the security management of risk zones, such as official buildings in the conflict area. In this paper, we propose an automatic checkpoint system that verifies persons using information from ID cards and facial features. The methods for a person’s information abstraction and verification are introduced based on useful information such as ID number and name, extracted from official cards, and facial images from videos. The proposed system shows promising results and has a real impact on the local society.

Keywords: face comparison, card recognition, OCR, checkpoint system, authentication

Procedia PDF Downloads 299

Authors: Aishrith Rao

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Human activity recognition is an important aspect of video analytics, and many approaches have been recommended to enable action recognition. In this approach, the model is used to identify the action of the multiple people in the frame and classify them accordingly. A few approaches use RNNs and 3D CNNs, which are computationally expensive and cannot be trained with the small datasets which are currently available. Multi-person action recognition has been performed in order to understand the positions and action of people present in the video frame. The size of the video frame can be adjusted as a hyper-parameter depending on the hardware resources available. OpenPose has been used to calculate pose estimate using CNN to produce heap-maps, one of which provides skeleton features, which are basically joint features. The features are then extracted, and a classification algorithm can be applied to classify the action.

Keywords: human activity recognition, computer vision, pose estimates, convolutional neural networks

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Authors: Hyun June Kim, Tailong Shi, Seden Akdagli, Sam Most, Yuling Yan

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Quantitative analysis of mouse whisker movement can be used to study functional recovery and regeneration of facial nerve after an injury. However, it is challenging to accurately track mouse whisker movements, and most whisker tracking methods require manual intervention, e.g. fixing the head of the mouse during a study. Here we describe a semi-automated image processing method that is applied to high-speed video recordings of free-moving mice to track whisker movements. We first track the head movement of a mouse by delineating the lower head contour frame-by-frame to locate and determine the orientation of its head. Then, a region of interest is identified for each frame, with subsequent application of the Hough transform to track individual whisker movements on each side of the head. Our approach is used to examine the functional recovery of damaged facial nerves in mice over a course of 21 days.

Keywords: mystacial macrovibrissae, whisker tracking, head tracking, facial nerve recovery

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Authors: A. S. Bouchikhi, A. Megueni, S. Habibi

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One major problem when using bonded Fiber Reinforced Polymer is the presence of high inter facial stresses near the end of the composite laminate which might govern the failure of the strengthening schedule. It is known that the decrease of FRP plate thickness and the fitness of adhesive reduce the stress concentration at plate ends. Another way is to use a plate with a non uniform section or tapered ends and softer adhesive at the edges. In this paper, a comprehensive finite element (FE) study has been conducted to investigate the effect of mixed adhesive joints (MAJ) and tapering plate on the inter facial stress distribution in the adhesive layer, this paper presents the results of a study of application of two adhesives with different stiffnesses (bi-adhesive) along the joint strength length between the CFRP-strengthened steel beam for tapered and untapered plate on the distribution of inter facial stresses. A stiff adhesive was applied in the middle portion of the joint strength, while a low modulus adhesive was applied towards the edges prone to stress concentrations.

Keywords: FRP, mixed adhesive joints, stresses, tapered plate, retrofitted beams bonded

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Authors: Lilah Inzelberg, David Rand, Stanislav Steinberg, Moshe David Pur, Yael Hanein

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Human facial expressions carry important psychological and neurological information. Facial expressions involve the co-activation of diverse muscles. They depend strongly on personal affective interpretation and on social context and vary between spontaneous and voluntary activations. Smiling, as a special case, is among the most complex facial emotional expressions, involving no fewer than 7 different unilateral muscles. Despite their ubiquitous nature, smiles remain an elusive and debated topic. Smiles are associated with happiness and greeting on one hand and anger or disgust-masking on the other. Accordingly, while high-resolution recording of muscle activation patterns, in a non-interfering setting, offers exciting opportunities, it remains an unmet challenge, as contemporary surface facial electromyography (EMG) methodologies are cumbersome, restricted to the laboratory settings, and are limited in time and resolution. Here we present a wearable and non-invasive method for objective mapping of facial muscle activation and demonstrate its application in a natural setting. The technology is based on a recently developed dry and soft electrode array, specially designed for surface facial EMG technique. Eighteen healthy volunteers (31.58 ± 3.41 years, 13 females), participated in the study. Surface EMG arrays were adhered to participant left and right cheeks. Participants were instructed to imitate three facial expressions: closing the eyes, wrinkling the nose and smiling voluntary and to watch a funny video while their EMG signal is recorded. We focused on muscles associated with 'enjoyment', 'social' and 'masked' smiles; three categories with distinct social meanings. We developed a customized independent component analysis algorithm to construct the desired facial musculature mapping. First, identification of the Orbicularis oculi and the Levator labii superioris muscles was demonstrated from voluntary expressions. Second, recordings of voluntary and spontaneous smiles were used to locate the Zygomaticus major muscle activated in Duchenne and non-Duchenne smiles. Finally, recording with a wireless device in an unmodified natural work setting revealed expressions of neutral, positive and negative emotions in face-to-face interaction. The algorithm outlined here identifies the activation sources in a subject-specific manner, insensitive to electrode placement and anatomical diversity. Our high-resolution and cross-talk free mapping performances, along with excellent user convenience, open new opportunities for affective processing and objective evaluation of facial expressivity, objective psychological and neurological assessment as well as gaming, virtual reality, bio-feedback and brain-machine interface applications.

Keywords: affective expressions, affective processing, facial EMG, high-resolution electromyography, independent component analysis, wireless electrodes

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Authors: S. Shujan, A. T. Rupasinghe, N. L. Gunawardena

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Numerous studies have determined that there is a direct correlation between the successful interviewee and the nonverbal behavioral patterns of that person during the interview. In this study, we focus on formations of interview questions in such a way that, it gets an opportunity for assessing interviewee through the answers using the nonverbal behavioral cues. From all the nonverbal behavioral factors we have identified, in this study priority is given to the ‘facial expression variations’ with the assistance of facial expression analytics tool; this research proposes a novel approach in question formation for the assessment of interviewees in ‘Software Industry’.

Keywords: assessments, hirability, interviews, non-verbal behaviour patterns, question formation

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Authors: H. G. C. P. Dinesh, G. Tharshini, M. P. B. Ekanayake, G. M. R. I. Godaliyadda

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This paper presents a new spatial feature extraction method based on principle component analysis (PCA) and Fisher Discernment Analysis (FDA) for facial expression recognition. It not only extracts reliable features for classification, but also reduces the feature space dimensions of pattern samples. In this method, first each gray scale image is considered in its entirety as the measurement matrix. Then, principle components (PCs) of row vectors of this matrix and variance of these row vectors along PCs are estimated. Therefore, this method would ensure the preservation of spatial information of the facial image. Afterwards, by incorporating the spectral information of the eigen-filters derived from the PCs, a feature vector was constructed, for a given image. Finally, FDA was used to define a set of basis in a reduced dimension subspace such that the optimal clustering is achieved. The method of FDA defines an inter-class scatter matrix and intra-class scatter matrix to enhance the compactness of each cluster while maximizing the distance between cluster marginal points. In order to matching the test image with the training set, a cosine similarity based Bayesian classification was used. The proposed method was tested on the Cohn-Kanade database and JAFFE database. It was observed that the proposed method which incorporates spatial information to construct an optimal feature space outperforms the standard PCA and FDA based methods.

Keywords: facial expression recognition, principle component analysis (PCA), fisher discernment analysis (FDA), eigen-filter, cosine similarity, bayesian classifier, f-measure

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Authors: Chi H. Lin, Chi C. Lin, Chih L. Hsieh

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Motor Imagery (MI) alone or combined with action observation (AO) has been shown to enhance motor performance and skill learning. The most effective way to combine these techniques has received limited scientific scrutiny. In the present study, we examined the effects of simultaneous (i.e., observing an action whilst imagining carrying out the action concurrently), alternate (i.e., observing an action and then doing imagery related to that action consecutively) and synthesis (alternately perform action observation and imagery action and then perform observation and imagery action simultaneously) AOMI combinations on improving golf putting performance and learning. Participants, 45 university students who had no formal experience of using imagery for the study, were randomly allocated to one of four training groups: simultaneous action observation and motor imagery (S-AOMI), alternate action observation and motor imagery (A-AOMI), synthesis action observation and motor imagery (A-S-AOMI), and a control group. And it was applied 'Different Experimental Groups with Pre and Post Measured' designs. Participants underwent eighteen times of different interventions, which were happened three times a week and lasting for six weeks. We analyzed the information we received based on two-factor (group × times) mixed between and within analysis of variance to discuss the real effects on participants' golf putting performance and learning about different intervention methods of different types of combined action observation and motor imagery. After the intervention, we then used imagery questionnaire and journey to understand the condition and suggestion about different motor imagery and action observation intervention from the participants. The results revealed that the three experimental groups both are effective in putting performance and learning but not for the control group, and the A-S-AOMI group is significantly better effect than S-AOMI group on golf putting performance and learning. The results confirmed the effect of motor imagery combined with action observation on the performance and learning of golf putting. In particular, in the groups of synthesis, motor imagery, or action observation were alternately performed first and then performed motor imagery, and action observation simultaneously would have the best effectiveness.

Keywords: motor skill learning, motor imagery, action observation, simulation

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Authors: Amin Derakhshan, Mohammad Mikaili, Mohammad Ali Khalilzadeh, Amin Mohammadian

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This paper proposes a stress recognition system from multi-modal bio-potential signals. For stress recognition, Support Vector Machines (SVM) and LDA are applied to design the stress classifiers and its characteristics are investigated. Using gathered data under psychological polygraph experiments, the classifiers are trained and tested. The pattern recognition method classifies stressful from non-stressful subjects based on labels which come from polygraph data. The successful classification rate is 96% for 12 subjects. It means that facial thermal imaging due to its non-contact advantage could be a remarkable alternative for psycho-physiological methods.

Keywords: stress, thermal imaging, face, SVM, polygraph

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Authors: Xiaoyuan Suo

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3D object reconstruction is a broad research area within the computer vision field involving many stages and still open problems. One of the existing challenges in this field lies with micromotion, such as the facial expressions on the appearance of the human or animal face. Similar literatures in this field focuses on 3D reconstruction in stable conditions such as an existing image or photos taken in a rather static environment, while the purpose of this work is to discuss a flexible scan system using multiple cameras that can correctly reconstruct 3D stable and moving objects -- human face with expression in particular. Further, a mathematical model is proposed at the end of this literature to automate the 3D object reconstruction process. The reconstruction process takes several stages. Firstly, a set of simple 2D lines would be projected onto the object and hence a set of uneven curvy lines can be obtained, which represents the 3D numerical data of the surface. The lines and their shapes will help to identify object’s 3D construction in pixels. With the two-recorded angles and their distance from the camera, a simple mathematical calculation would give the resulting coordinate of each projected line in an absolute 3D space. This proposed research will benefit many practical areas, including but not limited to biometric identification, authentications, cybersecurity, preservation of cultural heritage, drama acting especially those with rapid and complex facial gestures, and many others. Specifically, this will (I) provide a brief survey of comparable techniques existing in this field. (II) discuss a set of specialized methodologies or algorithms for effective reconstruction of 3D objects. (III)implement, and testing the developed methodologies. (IV) verify findings with data collected from experiments. (V) conclude with lessons learned and final thoughts.

Keywords: 3D photogrammetry, 3D object reconstruction, facial expression recognition, facial recognition

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Authors: Avyarthana Dey, Naren P. Rao, Arpitha Jacob, Chaitra V. Hiremath, Shivarama Varambally, Ganesan Venkatasubramanian, Rose Dawn Bharath, Bangalore N. Gangadhar

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Objective: Impaired facial emotion recognition is widely reported in schizophrenia. Neuropeptide oxytocin is known to modulate brain regions involved in facial emotion recognition, namely amygdala, in healthy volunteers. However, its effect on facial emotion recognition deficits seen in schizophrenia is not well explored. In this study, we examined the effect of intranasal OXT on processing facial emotions and its neural correlates in patients with schizophrenia. Method: 12 male patients (age= 31.08±7.61 years, education= 14.50±2.20 years) participated in this single-blind, counterbalanced functional magnetic resonance imaging (fMRI) study. All participants underwent three fMRI scans; one at baseline, one each after single dose 24IU intranasal OXT and intranasal placebo. The order of administration of OXT and placebo were counterbalanced and subject was blind to the drug administered. Participants performed a facial emotion recognition task presented in a block design with six alternating blocks of faces and shapes. The faces depicted happy, angry or fearful emotions. The images were preprocessed and analyzed using SPM 12. First level contrasts comparing recognition of emotions and shapes were modelled at individual subject level. A group level analysis was performed using the contrasts generated at the first level to compare the effects of intranasal OXT and placebo. The results were thresholded at uncorrected p < 0.001 with a cluster size of 6 voxels. Neuropeptide oxytocin is known to modulate brain regions involved in facial emotion recognition, namely amygdala, in healthy volunteers. Results: Compared to placebo, intranasal OXT attenuated activity in inferior temporal, fusiform and parahippocampal gyri (BA 20), premotor cortex (BA 6), middle frontal gyrus (BA 10) and anterior cingulate gyrus (BA 24) and enhanced activity in the middle occipital gyrus (BA 18), inferior occipital gyrus (BA 19), and superior temporal gyrus (BA 22). There were no significant differences between the conditions on the accuracy scores of emotion recognition between baseline (77.3±18.38), oxytocin (82.63 ± 10.92) or Placebo (76.62 ± 22.67). Conclusion: Our results provide further evidence to the modulatory effect of oxytocin in patients with schizophrenia. Single dose oxytocin resulted in significant changes in activity of brain regions involved in emotion processing. Future studies need to examine the effectiveness of long-term treatment with OXT for emotion recognition deficits in patients with schizophrenia.

Keywords: recognition, functional connectivity, oxytocin, schizophrenia, social cognition

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Authors: Isa Moazen, Ali Nahvi

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Driver drowsiness is a major cause of vehicle accidents, and facial images are highly valuable to detect drowsiness. In this paper, we perform our research via a thermal camera to record drivers' facial images on a driving simulator. A robust real-time algorithm extracts the features using horizontal and vertical integration projection, contours, contour orientations, and cropping tools. The features are included four target areas on the cheeks and forehead. Qt compiler and OpenCV are used with two cameras with different resolutions. A high-resolution thermal camera is used for fifteen subjects, and a low-resolution one is used for a person. The results are investigated by four temperature plots and evaluated by observer rating of drowsiness.

Keywords: advanced driver assistance systems, thermal imaging, driver drowsiness detection, feature extraction

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Authors: Shivani Dhande, Sanjiv Choudhary, Adarshlata Singh

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Introduction: Chemical peeling is a popular, relatively inexpensive day procedure and generally safe method for treatment of pigmentary skin disorders and for skin rejuvenation. Chemical peels are classified by the depth of action into superficial, medium, and deep peels.Various facial pigmentary conditions have significant impact on quality of life causing psychological stress, necessitating its safe and effective treatment.Aim & Objectives:To compare the efficacy of Salicylic acid, Trichloroaceticacid & Glycolic Acid in facial melanosis(melasma,photomelanosis& post acne pigmentation).To study the side effects of above mentioned peeling agents. Method and Materials:It was a randomized parallel control single blind study consisting of total of 36 cases, 12 cases each of melasma, photo melanosis and post acne pigmentation within age group 20-50 years having fitzpatrick’s skin type4. Woods lamp examination was done to confirm the type of melasma.Patients with keloidal tendency, active herpes infection or past history of hypersensitivity to salicylic acid, trichloroaceticand glycolic acid as well aspatients on systemic isotretinoin were excluded.Clinical photographs at the beginning of therapy and then serially, were taken to assess the clinical response. Prior to application a written informed consent was obtained. A post auricular test peel was performed. Patients were divided into 3 groups, containing 12 patients each of melasma, photomelanosis and post acnepigmentation.All the three peels SA peel 20% (done once in 2 weeks), GA peel 50% (done once in 3 weeks) and TCA 15% (done once in 3 weeks) were used with total six settings for each patient. Before application of peel patients were counseled to wash the face with soap and water. Then face was dried and cleaned with spirit and acetone to remove all cutaneous oils. GA, TCA, SA were applied with cotton buds/gauze withmild strokes. After a contact period off 5-10mins neutralization was done with cold water. Post peel topical sunscreen application was mandatory. MASI was used pre and post treatment to assess melasma. Investigator’s global improvement scale- overall hyperpigmentation (4-significant, 3-moderate, 2-mild, 1-minimal, 0-no change ) and Patient’s satisfaction grading scale (>70%- excellent response, 50-70%- good response, <50%- average response) was used to assess improvement in all the three facial melanosis.Results:In our study of 12 patients of melasma, 4 (33.33%)patients showed excellent results;3 (25%) with GAand 1(8.33%) of TCA.Good response was seen in 4 (33.33%) patients;1(8.33%) each for GA & SA and 2(16.66%) for TCA.Poor response was seen in 4(33.33%) patients;1(8.33%) for TCA and 3 (25%) for SA.Of 12 patients of photomelanosis, excellent resultswas seen in 3(25%)patients of TCA. Good response was seen in 4 (33.33%) patients, 1(8.33%) each of TCA &SA and 2(16.66%) of GA.Poor responsewas seen in 5(41.66%) patients;3 (25%) for SA and 2(16.66%) of GA.Of 12 patients of post acne pigmentation, excellent responsein 3 (25%) patients;2(16.66%) of SA and 1(8.33%) of TCA.Good responsewas seen in 5(41.66%) patients;2(16.66%) of SA and GA and1(8.33%) of TCA.Poor response was seen in 4 (33.33%) patients; 2 (16.66%) for SA and TCA both. No major side effects in the form of scarring or persistant pigmentation was seen. Transient blackening of skin with burning sensation was seen in cases treated with TCA and SA. Post procedural itching and redness was noted with GA peel. Conclusion- In our study GA(50%),TCA(15%) & SA(20%) peels showed excellent response in melasma, photomelanosis and post-acne pigmentation respectively.All the 3 peeling agents were well tolerated without any significant side-effects in the above specified concentrations.

Keywords: facial melanosis, gycolic acid, salicylic acid, trichloroacetic acid

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Authors: Stefania Arguelles Reyes, Octavio José Salcedo Parra, Alberto Acosta López

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This paper presents a web application for the improvement of images through recognition. The web application is based on the analysis of picture-based recognition methods that allow an improvement on the physical appearance of people posting in social networks. The basis relies on the study of tools that can correct or improve some features of the face, with the help of a wide collection of user images taken as reference to build a facial profile. Automatic facial profiling can be achieved with a deeper study of the Object Detection Library. It was possible to improve the initial images with the help of MATLAB and its filtering functions. The user can have a direct interaction with the program and manually adjust his preferences.

Keywords: Matlab, make up, recognition methods, web application

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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: Fatima Akhmedova, Simon Liao

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One of the most critical decision points in the design of a face recognition system is the choice of an appropriate face representation. Effective feature descriptors are expected to convey sufficient, invariant and non-redundant facial information. In this work, we propose a set of Hahn moments as a new approach for feature description. Hahn moments have been widely used in image analysis due to their invariance, non-redundancy and the ability to extract features either globally and locally. To assess the applicability of Hahn moments to Face Recognition we conduct two experiments on the Olivetti Research Laboratory (ORL) database and University of Notre-Dame (UND) X1 biometric collection. Fusion of the global features along with the features from local facial regions are used as an input for the conventional k-NN classifier. The method reaches an accuracy of 93% of correctly recognized subjects for the ORL database and 94% for the UND database.

Keywords: face recognition, Hahn moments, recognition-by-parts, time-lapse

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Authors: F. Loffredo, M. Quarto, M. Pugliese, A. Mazzella, F. De Cicco, V. Roca

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The aim of this study is to evaluate the efficacy of radon remedial action in a school on the Ischia island, South Italy, affected by indoor radon concentration higher than the value of 500 Bq/m³. This value is the limit imposed by the Italian legislation, to above which corrective actions in schools are necessary. Before the application of remedial action, indoor radon concentrations were measured in 9 rooms of the school. The measurements were performed with LR-115 passive alpha detectors (SSNTDs) and E-Perm. The remedial action was conducted in one of the office affected by high radon concentration using a Radonstop paint applied after the construction of a concrete slab under the floor. The effect of remedial action was the reduction of the concentration of radon of 41% and moreover it has demonstrated to be durable over time. The chosen method is cheap and easy to apply and it could be designed for various types of building. This method can be applied to new and existing buildings that show high dose values.

Keywords: E-Perm, LR 115 detectors, radon remediation, school

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Authors: En Hyung Kim

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Partial unilateral lentiginosis (PUL) is an unusual pigmentary disorder characterized by numerous lentigines grouped within an area of normal skin. Although treatment is not necessary, many patients with facial PUL seek medical help for cosmetic reasons. There is no established standard treatment for PUL. Conventional lasers may cause postinflammatory hyperpigmentation because keratinocytes are injured during the process. Also scarring, long downtime and pain are important issues. Case: A 19-year-old patient with facial PUL was treated with 1064-nm Q-Switched Neodymium-Doped Yttrium Aluminum Garnet (QS Nd:YAG) laser. The patient was treated at one-week intervals starting with a spot size of 6 mm, a fluence of 2.5 J/cm2 and a pulse rate of 10 Hz with 1-2 passes of slow sliding technique with approximately 5-15 % overlap. The fluence was elevated to 3 J/cm2 after the 4th session according to treatment response and patient tolerance. After 10 treatment sessions the lesions were remarkably improved. Discussion: Although the exact mechanism by which low fluence 1,064-nm QS Nd:YAG laser improves pigmentary lesions is unclear, the term ‘subcellular selective photothermolysis’ and ‘melanocyte apoptosis and replacement’ have been proposed. If appropriate measures are taken to monitor patient response during and after the procedure, low fluence 1064-nm QS Nd:YAG laser may achieve good cosmetic result in the treatment of PUL with a very safe and effective profile.

Keywords: laser toning, low fluence, 1064-nm Q-switched neodymium-doped yttrium aluminum garnet laser, partial unilateral lentiginosis

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Authors: Ki Moo Lim, Iman R. Tayibnapis

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According to WHO estimation, 38 out of 56 million (68%) global deaths in 2012, were due to noncommunicable diseases (NCDs). To avert NCD, one of the solutions is early detection of diseases. In order to do that, we developed 'U-Healthcare Mirror', which is able to measure vital sign such as heart rate (HR) and respiration rate without any physical contact and consciousness. To measure HR in the mirror, we utilized digital camera. The camera records red, green, and blue (RGB) discoloration from user's facial image sequences. We extracted blood volume pulse (BVP) from the RGB discoloration because the discoloration of the facial skin is accordance with BVP. We used blind source separation (BSS) to extract BVP from the RGB discoloration and adaptive filters for removing noises. We utilized singular value decomposition (SVD) method to implement the BSS and the adaptive filters. HR was estimated from the obtained BVP. We did experiment for HR measurement by using our method and previous method that used independent component analysis (ICA) method. We compared both of them with HR measurement from commercial oximeter. The experiment was conducted under various distance between 30~110 cm and light intensity between 5~2000 lux. For each condition, we did measurement 7 times. The estimated HR showed 2.25 bpm of mean error and 0.73 of pearson correlation coefficient. The accuracy has improved compared to previous work. The optimal distance between the mirror and user for HR measurement was 50 cm with medium light intensity, around 550 lux.

Keywords: blood volume pulse, heart rate, photoplethysmography, independent component analysis

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Authors: M. N. Abu Seman, L. M. Kei, M. A. Yusoff

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Forward Osmosis (FO) polyamide thin-film composite membranes have been prepared by inter facial polymerization using commercial UF polyethersulfone as membrane support. Different inter facial polymerization times (10s, 30s and 60s) in the organic solution containing trimesoyl chloride (TMC) at constant m-phenylenediamine (MPD) concentration (2% w/v) were studied. The synthesized polyamide membranes then tested for treatment of natural organic matter (NOM) and compared to commercial Cellulose TriAcetate (CTA) membrane. It was found that membrane prepared with higher reaction time (30 s and 60 s) exhibited better membrane performance (flux and humic acid removal) over commercial CTA membrane.

Keywords: cellulose triacetate, forward osmosis, humic acid, polyamide

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Authors: Dumasari, Pujiati Utami

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The bargaining position is important for a craftsman in every transaction. A strong bargaining position to encourage craftsmen to gain feasible prices on souvenirs tourism products are sold in several market segments. Some social actions of craftsmen turned out to also determine the conditions bargaining. The main goal of this study is to assess the range of social action to strengthen the bargaining position of craftsmen in marketing various products of tourism souvenir. Location of the study is set intentionally in the Sub-District of Baturaden, Banyumas Regency and also the Sub-District of Purbalingga Wetan, Purbalingga Regency. Both of them are located in the Central Java Province, Indonesia. The research method is the descriptive case study. The results showed that the craftsmen not only carry out one or two type of social action. They do all of the social action: the first is rational based instrumental, the second is rational based on the values, the third is affective, and the fourth is traditional. However, craftsmen also develop other social actions namely: collective, productive and creative action. At respondents in Baturaden dominant type of social action that is instrumentally rational, productive and creative. Meanwhile, respondents in Purbalingga more dominant social action collective, productive and creative. Some social actions implemented simultaneously by the respondents. Because of this, they concluded that the rational action that modified by themselves is more easily for strengthening the bargaining position when facing the craftsmen traders collectors. Collective and rationality social action has the highest sensitivity value for strengthening the bargaining position of craftsmen.

Keywords: bargaining position, craftsmen, strengthen, social actions, marketing of tourism souvenir

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Authors: Ayat E. Ali, Christeen R. Aziz, Merna A. Helmy, Mohammed M. Malek, Sherif H. El-Gohary

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Goal: Purpose of the project was to make a plastic surgery prediction by using pre-operative images for the plastic surgeries’ patients and to show this prediction on a screen to compare between the current case and the appearance after the surgery. Methods: To this aim, we implemented a software which used data from the internet for facial skin diseases, skin burns, pre-and post-images for plastic surgeries then the post- surgical prediction is done by using K-nearest neighbor (KNN). So we designed and fabricated a smart mirror divided into two parts a screen and a reflective mirror so patient's pre- and post-appearance will be showed at the same time. Results: We worked on some skin diseases like vitiligo, skin burns and wrinkles. We classified the three degrees of burns using KNN classifier with accuracy 60%. We also succeeded in segmenting the area of vitiligo. Our future work will include working on more skin diseases, classify them and give a prediction for the look after the surgery. Also we will go deeper into facial deformities and plastic surgeries like nose reshaping and face slim down. Conclusion: Our project will give a prediction relates strongly to the real look after surgery and decrease different diagnoses among doctors. Significance: The mirror may have broad societal appeal as it will make the distance between patient's satisfaction and the medical standards smaller.

Keywords: k-nearest neighbor (knn), face detection, vitiligo, bone deformity

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Authors: Xiaosheng Chen, Jingjing Chen, Phil Reed, Dan Zhang

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Conscious intention can be a promising point cut to grasp consciousness and orient voluntary action. The current study adopted a random ratio (RR), yoked random interval (RI) reinforcement learning schedule instead of the previous highly repeatable and single decision point paradigms, aimed to induce voluntary action with the conscious intention that evolves from the interaction between short-range-intention and long-range-intention. Readiness potential (RP) -like-EEG amplitude and inter-trial-EEG variability decreased significantly prior to voluntary action compared to cued action for inter-trial-EEG variability, mainly featured during the earlier stage of neural activities. Notably, (RP) -like-EEG amplitudes decreased significantly prior to higher RI-reward rates responses in which participants formed a higher plane of conscious intention. The present study suggests the possible contribution of conscious intention-based processes to the neural activities from the earlier stage prior to voluntary action on reinforcement leanring schedule.

Keywords: Reinforcement leaning schedule, voluntary action, EEG, conscious intention, readiness potential

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Authors: Finn Lannon, Jenny Roth, Roland Deutsch, Eric Igou

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The world continues to be rife with economic inequality, which has an impact on how people think and behaves in response to large and often growing gaps in wealth. Large gaps in earnings between groups within a particular organization, area or society can create tension between groups. Collective action tendencies (to protest, sign a petition, vote on behalf of an ingroup etc.) are also a growing phenomenon globally. Research shows that economic inequality promotes social processes such as appraisals of illegitimacy, which are recognized antecedents of collective action. This paper examines different types of collective action intentions among middle-status group members in response to economic inequality in two studies. Study 1 (N = 72) demonstrates a causal link between high economic inequality and collective action intentions of middle-status group members both to reduce inequality and to improve group status. A second pre-registered study (N = 432) examines key drivers of these relationships, including illegitimacy appraisals and direction of intergroup comparison. Adding to the current understanding of the topic, distinctions between the illegitimacy of one’s group status and the illegitimacy of societal inequality are found to mediate key relationships between economic inequality and relevant collective action types. The direction of intergroup comparison (upwards vs. downwards) is also shown to have a significant impact on collective action intentions to improve group status. Findings add to the understanding of the consequences of economic inequality and drivers of collective action intentions.

Keywords: economic inequality, collective action, legitimacy, social psychology

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Authors: Monica Alzate, Marcos Dono, Jose Manuel Sabucedo

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As long as collective action and its predictors constitute a big body of work in the field of political psychology, context-dependent studies and moral variables are a relatively new issue. The main goal of this presentation is to examine the differences in the predictors of collective action when taking into account two different types of protest, and also focus on the role of moral obligation as a predictor of collective action. To do so, we sampled both protesters and non-protesters from two mobilizations (N=376; N=563) of different nature (catalan Independence, and an 'indignados' march) and performed a logistic regression and a 2x2 MANOVA analysis. Results showed that the predictive variables that were more discriminative between protesters and non-protesters were identity, injustice, efficacy and moral obligation for the catalan Diada and injustice and moral obligation for the 'indignados'. Also while the catalans scored higher in the identification and efficacy variables, the indignados did so in injustice and moral obligation. Differences are evidenced between two types of collective action that coexist within the same protest cycle. The frames of injustice and moral obligation gain strength in the post-2010 mobilizations, a fact probably associated with the combination of materialist and post-materialist values that distinguish the movement. All of this emphasizes the need of studying protest from a contextual point of view. Besides, moral obligation emerges as key predictor of collective action engagement.

Keywords: collective action, identity, moral obligation, protest

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Authors: Maha Saliba Foster

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Speech perception has been recognized as a bi-sensory process involving the auditory and visual channels. Compared to the auditory modality, the contribution of the visual signal to speech perception is not very well understood. Studying how the visual modality affects speech recognition can have pedagogical implications in second language learning, as well as clinical application in speech therapy. The current investigation explores the potential effect of speech visual cues on the perception of Arabic emphatics (AEs). The corpus consists of 36 minimal pairs each containing two contrasting consonants, an AE versus a non-emphatic (NE). Movies of four Lebanese speakers were edited to allow perceivers to have partial view of facial regions: lips only, lips-cheeks, lips-chin, lips-cheeks-chin, lips-cheeks-chin-neck. In the absence of any auditory information and relying solely on visual speech, perceivers were above chance at correctly identifying AEs or NEs across vowel contexts; moreover, the models were able to predict the probability of perceivers’ accuracy in identifying some of the COIs produced by certain speakers; additionally, results showed an overlap between the measurements selected by the computer and those selected by human perceivers. The lack of significant face effect on the perception of AEs seems to point to the lips, present in all of the videos, as the most important and often sufficient facial feature for emphasis recognition. Future investigations will aim at refining the analyses of visual cues used by perceivers by using Principal Component Analysis and including time evolution of facial feature measurements.

Keywords: Arabic emphatics, machine learning, speech perception, visual speech perception

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Authors: Amira D. Ali

Abstract:

Action research studies in education often address learners’ needs and empower practitioner-researcher to effectively change instructional practices and school communities. A systematic review of action research (AR) studies undertaken in EFL/ESL settings was conducted in this paper to systematically analyze empirical studies on action research published within a ten-year period (between 2010 and 2019). The review also aimed at investigating the focal strategies in teaching the language skills at school level and evaluating the overall quality of AR studies concerning focus, purpose, methodology and contribution. Inclusion criteria were established and 41 studies that fit were finally selected for the systematic review. Garrard’s (2007) Matrix Method was used to structure and synthesize the literature. Results showed a significant diversity in teaching strategies and implementation of the AR model. Almost a quarter of the studies focused on improving writing skills at elementary school level. In addition, findings revealed that (44%) of the studies used a mixed approach followed by qualitative method approach (41%), whereas only (15%) employed quantitative methodology. Research gaps for future action research in developing language skills were pointed out, and recommendations were offered.

Keywords: action research, EFL/ESL context, language skills, systematic review

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Authors: Erick C. Valverde, Wansu Lim

Abstract:

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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