• Journal of Multimedia Information System
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• v.5 no.1
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• pp.15-20
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• 2018

There are a lot of problems in the face detection area. One of them is detecting faces by facial features and reducing number of the false negatives and positions. This paper is directed to solve this problem by the proposed triangle method. Also, this paper explans cascades, Haar-like features, AdaBoost, HOG. We propose a scheme using 12-net, 24-net, 48-net to scan images and improve efficiency. Using triangle method for frontal pose, B and B1 methods for other poses in neural networks are proposed.

• International Journal of Contents
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• v.8 no.1
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• pp.16-22
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• 2012

In this paper we propose a method for verifying video in a video telephony system implemented in DM6446 DaVinci Processor. Each frame is categorized either error free frame or error frame depending on the predefined criteria. Human face is chosen as a basic means for authenticating the video frame. Skin color based algorithm is implemented for detecting the face in the video frame. The video frame is classified as error free frame if there is single face object with clear view of facial features (eyes, nose, mouth etc.) and the background of the image frame is not different then the predefined background, otherwise it will be classified as error frame. We also implemented the image histogram based NCC (Normalized Cross Correlation) comparison for video verification to speed up the system. The experimental result shows that the system is able to classify frames with 90.83% of accuracy.

• Journal of Advanced Information Technology and Convergence
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• v.8 no.2
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• pp.47-58
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• 2018

In this paper, we propose a method for skin condition analysis using a camera module embedded in a smartphone without a separate skin diagnosis device. The type of skin disease detected in facial image taken by smartphone is acne, pigmentation, blemish and flush. Face features and regions were detected using Haar features, and skin regions were detected using YCbCr and HSV color models. Acne and flush were extracted by setting the range of a component image hue, and pigmentation was calculated by calculating the factor between the minimum and maximum value of the corresponding skin pixel in the component image R. Blemish was detected on the basis of adaptive thresholds in gray scale level images. As a result of the experiment, the proposed skin condition analysis showed that skin diseases of acne, pigmentation, blemish and flush were effectively detected.

• Journal of Genetic Medicine
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• v.18 no.1
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• pp.70-74
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• 2021

Cohen-Gibson syndrome (CGS) was first reported by Cohen et al., who identified the mutation of the gene encoding the embryonic ectoderm development (EED) in a patient with phenotypes similar to Weaver syndrome. CGS manifests as an overgrowth and intellectual disability, in addition to the characteristic facial features and organ anomalies. CGS has been reported in only 11 unrelated patients since 2015. A girl aged 6 years and 3 months presented with seizures. She had macrosomia, a dysmorphic face, and intellectual disability. Her mother and younger sister and brother also had macrosomia, intellectual disability, and similar facial features; additionally, her mother experienced seizures and had an arachnoid cyst, while her siblings had valvar pulmonary stenosis. Whole-exome sequencing for the proband revealed a mutation of EED (c.581A>G, p.Asn194Ser), which was also verified in the mother and both siblings using Sanger sequencing. This is the first report of familial CGS.

• Journal of Internet Computing and Services
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• v.3 no.6
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• pp.13-24
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• 2002

This paper presents an automatic approach to detect face and facial feature from face images based on the color information and deformable model. Skin color information has been widely used for face and facial feature diction since it is effective for object recognition and has less computational burden, In this paper, we propose how to compensates varying light condition and utilize the transformed YCbCr color model to detect candidates region of face and facial feature from color images, Moreover, the detected face facial feature areas are subsequently assigned to a initial condition of active contour model to extract optimal boundaries of face and facial feature by resolving initial boundary problem when the active contour is used, The experimental results show the efficiency of the proposed method, The face and facial feature information will be used for face recognition and facial feature descriptor.

• Archives of Plastic Surgery
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• v.39 no.6
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• pp.606-611
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• 2012

Background Facial fractures are infrequent in children and adolescents and have different clinical features from those in adults. The low incidence in children and adolescents reflects the flexibility and underdevelopment of their facial skeletons, as well as their more protected environments. Only a few reports have reviewed such patients in Korea. The authors performed a retrospective study to analyze the characteristics of facial fractures in the Korean pediatric population. Methods We conducted a retrospective review on a series of 741 patients, aged <18 years, with facial fractures who had been treated at our hospital between 2006 and 2010. The following parameters were evaluated: age, sex, cause, location and type of fractures, associated injuries, treatment and complications. Results A total of 741 consecutive patients met the inclusion criteria. The ratio of boys to girls was 5.7:1. Facial fractures most commonly occurred in patients between 13 and 15 years of age (36.3%). The most common causes of injury was violence. The nasal fracture was the most common type of fracture (69%) and the blowout fracture was the second most common (20%). Associated injuries occurred in 156 patients (21%). Conclusions The incidence of pediatric facial fractures caused by violence is high in Korea. Our results show that as age increases, etiological factors and fracture patterns gradually shift towards those found in adults. This study provides an overview of facial fractures in these age groups that helps illustrate the trends and characteristics of the fractures and may be helpful in further evaluation and management.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.5
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• pp.535-543
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• 2002

In this paper, we propose a new gaze detection method using 2-D facial images captured by a camera on top of the monitor. We consider only the facial rotation and translation and not the eyes' movements. The proposed method computes the gaze point caused by the facial rotation and the amount of the facial translation respectively, and by combining these two the final gaze point on a monitor screen can be obtained. We detected the gaze point caused by the facial rotation by using a neural network(a multi-layered perceptron) whose inputs are the 2-D geometric changes of the facial features' points and estimated the amount of the facial translation by image processing algorithms in real time. Experimental results show that the gaze point detection accuracy between the computed positions and the real ones is about 2.11 inches in RMS error when the distance between the user and a 19-inch monitor is about 50~70cm. The processing time is about 0.7 second with a Pentium PC(233MHz) and 320${\times}$240 pixel-size images.

• Imaging Science in Dentistry
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• v.50 no.3
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• pp.255-260
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• 2020

Acquired facial lipoatrophy is a rare disease with an unclear etiology and pathological pathway. The distinct causative factors of this disease have been not elucidated, but it is suspected to be associated with immune system-related diseases, most notably AIDS. Although the management of facial lipoatrophy is very important for patients' social life and mental health, no treatment framework has been developed due to the unknown nature of the disease manifestation. The present case report was designed to provide sequential imaging to visualize the disease progression. The clinical backgrounds of the patients are also introduced, helping characterize this disease entity more clearly for maxillofacial specialists.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.1
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• pp.155-161
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• 2024

In this paper, we propose a new model by adding landmark information as a feature vector to the existing CNN-based facial emotion classification model. Facial emotion classification research using CNN-based models is being studied in various ways, but the recognition rate is very low. In order to improve the CNN-based models, we propose algorithms that improves facial expression classification accuracy by combining the CNN model with a landmark-based fully connected network obtained by ASM. By including landmarks in the CNN model, the recognition rate was improved by several percent, and experiments confirmed that further improved results could be obtained by adding FACS-based action units to the landmarks.

• Journal of Information Processing Systems
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• v.17 no.4
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• pp.754-771
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• 2021

In the task of continuous dimension emotion recognition, the parts that highlight the emotional expression are not the same in each mode, and the influences of different modes on the emotional state is also different. Therefore, this paper studies the fusion of the two most important modes in emotional recognition (voice and visual expression), and proposes a two-mode dual-modal emotion recognition method combined with the attention mechanism of the improved AlexNet network. After a simple preprocessing of the audio signal and the video signal, respectively, the first step is to use the prior knowledge to realize the extraction of audio characteristics. Then, facial expression features are extracted by the improved AlexNet network. Finally, the multimodal attention mechanism is used to fuse facial expression features and audio features, and the improved loss function is used to optimize the modal missing problem, so as to improve the robustness of the model and the performance of emotion recognition. The experimental results show that the concordance coefficient of the proposed model in the two dimensions of arousal and valence (concordance correlation coefficient) were 0.729 and 0.718, respectively, which are superior to several comparative algorithms.