• Journal of Information Processing Systems
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• v.9 no.1
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• pp.173-188
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• 2013

In Facial Expression Recognition Systems (FERS), only particular regions of the face are utilized for discrimination. The areas of the eyes, eyebrows, nose, and mouth are the most important features in any FERS. Applying facial features descriptors such as the local binary pattern (LBP) on such areas results in an effective and efficient FERS. In this paper, we propose an automatic facial expression recognition system. Unlike other systems, it detects and extracts the informative and discriminant regions of the face (i.e., eyes, nose, and mouth areas) using Haar-feature based cascade classifiers and these region-based features are stored into separate image files as a preprocessing step. Then, LBP is applied to these image files for facial texture representation and a feature-vector per subject is obtained by concatenating the resulting LBP histograms of the decomposed region-based features. The one-vs.-rest SVM, which is a popular multi-classification method, is employed with the Radial Basis Function (RBF) for facial expression classification. Experimental results show that this approach yields good performance for both frontal and near-frontal facial images in terms of accuracy and time complexity. Cohn-Kanade and JAFFE, which are benchmark facial expression datasets, are used to evaluate this approach.

• Journal of Information Processing Systems
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• v.17 no.2
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• pp.337-351
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• 2021

Automatically recognizing facial expressions in video sequences is a challenging task because there is little direct correlation between facial features and subjective emotions in video. To overcome the problem, a video facial expression recognition method using spatiotemporal recurrent neural network and feature fusion is proposed. Firstly, the video is preprocessed. Then, the double-layer cascade structure is used to detect a face in a video image. In addition, two deep convolutional neural networks are used to extract the time-domain and airspace facial features in the video. The spatial convolutional neural network is used to extract the spatial information features from each frame of the static expression images in the video. The temporal convolutional neural network is used to extract the dynamic information features from the optical flow information from multiple frames of expression images in the video. A multiplication fusion is performed with the spatiotemporal features learned by the two deep convolutional neural networks. Finally, the fused features are input to the support vector machine to realize the facial expression classification task. The experimental results on cNTERFACE, RML, and AFEW6.0 datasets show that the recognition rates obtained by the proposed method are as high as 88.67%, 70.32%, and 63.84%, respectively. Comparative experiments show that the proposed method obtains higher recognition accuracy than other recently reported methods.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.2
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• pp.131-136
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• 2004

According to development of media, various information is recorded in media, expression is one during interesting information. Because expression includes of relationship of human inside. Intention of inside is expressed by gesture, but expression has more information. And, expression can manufacture voluntarily, include plan of inside on the man. Also, expression has unique character in a person, have alliance that do division possibility. In this paper, to analyze expression of USB camera animation, wish to detect facial building block. Because characteristic point by person's expression change exists on face component. For component detection, in animation one frame with Capture, grasp facial position, and separate face area, and detect characteristic points of face component.

• International Journal of Internet, Broadcasting and Communication
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• v.7 no.2
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• pp.51-55
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• 2015

This paper proposes an algorithm for risk situation recognition using facial expression. The proposed method recognitions the surprise and fear expression among human's various emotional expression for recognizing dangerous situation. The proposed method firstly extracts the facial region using Harr-like technique from input, detects eye region and lip region from the extracted face. And then, the method applies Uniform LBP to each region, detects facial expression, and recognizes dangerous situation. The proposed method is evaluated for MUCT database image and web cam input. The proposed method produces good results of facial expression and discriminates dangerous situation well and the average recognition rate is 91.05%.

• Journal of Information Processing Systems
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• v.17 no.2
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• pp.399-410
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• 2021

Aiming at the problem that complex external variables in natural scenes have a greater impact on facial expression recognition results, a facial expression recognition method based on two-stream convolutional neural network is proposed. The model introduces exponentially enhanced shared input weights before each level of convolution input, and uses soft attention mechanism modules on the space-time features of the combination of static and dynamic streams. This enables the network to autonomously find areas that are more relevant to the expression category and pay more attention to these areas. Through these means, the information of irrelevant interference areas is suppressed. In order to solve the problem of poor local robustness caused by lighting and expression changes, this paper also performs lighting preprocessing with the lighting preprocessing chain algorithm to eliminate most of the lighting effects. Experimental results on AFEW6.0 and Multi-PIE datasets show that the recognition rates of this method are 95.05% and 61.40%, respectively, which are better than other comparison methods.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.12
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• pp.7187-7191
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• 2013

Most of the exogenous and endogenous chemical compounds are metabolized by enzymes of xenobiotic processing pathways, including the phase I cytochrome p450 species. Carcinogens and their metabolites are generally detoxified by phase II enzymes like glutathione-S-transferases (GST). The balance of enzymes determines whether metabolic activation of pro-carcinogens or inactivation of carcinogens occurs. Under certain conditions, deregulated expression of xenobiotic enzymes may also convert endogenous substrates to metabolites that can facilitate DNA adduct formation and ultimately lead to cancer development. In this study, we aimed to test the association between deregulation of metabolizing genes and brain tumorigenesis. The expression profile of metabolizing genes CYP1A1 and GSTP1 was therefore studied in a cohort of 36 brain tumor patients and controls using Western blotting. In a second part of the study we analyzed protein expression of GSTs in the same study cohort by ELISA. CYP1A1 expression was found to be significantly high (p<0.001) in brain tumor as compared to the normal tissues, with ~4 fold (OR=4, 95%CI=0.43-37) increase in some cases. In contrast, the expression of GSTP1 was found to be significantly low in brain tumor tissues as compared to the controls (p<0.02). This down regulation was significantly higher (OR=0.05, 95%CI=0.006-0.51; p<0.007) in certain grades of lesions. Furthermore, GSTs levels were significantly down-regulated (p<0.014) in brain tumor patients compared to controls. Statistically significant decrease in GST levels was observed in the more advanced lesions (III-IV, p<0.005) as compared to the early tissue grades (I-II). Thus, altered expression of these xenobiotic metabolizing genes may be involved in brain tumor development in Pakistani population. Investigation of expression of these genes may provide information not only for the prediction of individual cancer risk but also for the prevention of cancer.

• Journal of the Korea Society of Computer and Information
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• v.22 no.10
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• pp.151-157
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• 2017

In the case of uploading privacy information of an information owner in the Internet, the information owner may want to deliver the privacy information itself or remove such information from the search list in order to prevent third parties from accessing the privacy information of the information owner. Such a right to be forgotten may collide with the freedom of expression of a third party. The right to be forgotten, which originates from the self-determination right on privacy information based on Article 10 and 17 of the Constitution and the freedom of expression, which is based on Article 21 thereof are all relative basic rights and are both limited by Item 2 under Article 37 of the same law, which is the general limitation provision for the basic rights. Therefore, when the right to be forgotten and the freedom of expression collides, it is not possible to give priority to one of the those unilaterally. It depends on the nature of the case at hand to find a natural balance for the harmonious solution for both parties. The criteria can be the sensitivity to the privacy of the information owner caused by the disclose of the privacy information, the public benefits such information may serve, the social common good that could be expected by the disclosure of the privacy information and the damages suffered in terms of the personal interest caused by the disclosure of the information, in a comprehensive manner.

• Knowledge Management Research
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• v.18 no.3
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• pp.147-162
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• 2017

As social media started to work as important communication tools, social media users have tried to manage their image, identity, and impression through social media. Social media service providers have been interested in providing various functions effectively disclosing users' emotion, such as posting, commenting, and sharing content; on the other hand, relatively few efforts have been made to provide social media functions for information suppression. In this study, therefore, we attempt to examine the relationship between Facebook users' personality and impression management behaviors. Personal traits of users including public self-consciousness, positive self-expression, and honest self-expression were considered as independent variables. Impression management behaviors are composed of two variables, which are suppression and projection. The survey was conducted, targeting 230 Facebook users. The research findings show that public self-consciousness and positive self-expression are positively associated with information suppression while both positive and honest self-expression is positively associated with information projection.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.3
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• pp.681-694
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• 2018

This paper studied the effects of risk cognition of personal information and self-expression information on conation of privacy protection. In the first study, 88 college students who volunteered for this research were surveyed about risk cognition of personal information and conation to protect it. In the second study, after an information-seeking expert collected and organized the self-expression information that 88 volunteers had expressed on SNS, and then showed the organized self-expression information to 88 volunteers, and then 88 volunteers were surveyed about risk cognition of self-expression information and conation to protect it. As results of the first data analysis, the risk cognition of personal information had the greatest influence on non-disclosure of personal information, followed by reduction of the disclosure scope and law institutionalization requirement. As results of the second data analysis, SNS users openly expressed their opinion or life-style, but when they realized that self-expression information can be accumulated and become sensitive information, they had conation to protect their self-expression information such as non-disclosure, reduction of disclosure scope, and law institutionalization requirement. The implication of this study is that we have overcome the limitations of existing researches that can not explain information protection behavior on SNS.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.05a
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• pp.574-577
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• 2003

This paper manufactured animation to use expression for efficient action control of character animation. Animation to use expression is method to express natural animation little more easily and usefully in expression of motion. Find urea that could control animation in expression analyzing action control points of character and used in ceremony. Embodied animation to control automatically action of character on the basis of this. Efficiency of expression that animation by expression can create natural and realistic action by manufacturing that is simple was expose by advantage, but showed awkwardness than animation by key frame way by animator.