• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.5
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• pp.423-430
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• 2013

In typical face recognition systems, the frontal view of face is preferred to reduce the complexity of the recognition. Thus individuals may be required to stare into the camera, or the camera should be located so that the frontal images are acquired easily. However these constraints severely restrict the adoption of face recognition to wide applications. To alleviate this problem, in this paper, we address the problem of tracking and recognizing faces in video captured with no environmental control. The face tracker extracts a sequence of the angle/size normalized face images using IVT (Incremental Visual Tracking) algorithm that is known to be robust to changes in appearance. Since no constraints have been imposed between the face direction and the video camera, there will be various poses in face images. Thus the pose is identified using a PCA (Principal Component Analysis)-based pose classifier, and only the pose-matched face images are used to identify person against the pre-built face DB with 5-poses. For face recognition, PCA, (2D)PCA, and $(2D)^2PCA$ algorithms have been tested to compute the recognition rate and the execution time.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.1
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• pp.164-169
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• 2003

In this paper, we investigate recognition of human faces in a meeting room. The major challenges of identifying human faces in this environment include low quality of input images, poor illumination, unrestricted head poses and continuously changing facial expressions and occlusion. In order to address these problems we propose a novel algorithm, Dynamic Space Warping (DSW). The basic idea of the algorithm is to combine local features under certain spatial constraints. We compare DSW with the eigenface approach on data collected from various meetings. We have tested both front and profile face images and images with two stages of occlusion. As a result from the experiment, we obtained 82.7% for PCA algotithm, and 89.4% for DSW. We get to obtain 6.9% better result from conductive DSW approach rather than PCA. It turned out to be that it shows more original and unique facial image.

• Human Ecology Research
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• v.55 no.1
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• pp.45-55
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• 2017

This study analyzes diverse factors in time poverty and quality of life in dual-earner families with preschool children that pertain to the individual, family, and occupation. Data were taken from the 17th edition of the Korean Labor and Income Panel Study developed by the Korea Labor Institute in 2014. The sample consists of 826 households who are dual-earner families with preschool children. The major findings are as follows. First, this study identified inadequacies in personal care time for dual-earner families with preschool children. Second, the results show that gender, recognition of gender role, and overall satisfaction of occupation are related to the time poverty of dual-earner families. Men are more likely to experience time poverty than women, and equal recognition of gender role and satisfaction of occupation indicate a negative relation on the time poverty of dual-earner families with preschool children. Last, quality of life in non-time-poor groups is higher than for groups who experience time poverty. Also, health state, earned income, work-family life conflict, and overall satisfaction of occupation are commonly related to quality of life in both groups. The results suggest implications for comprehensive policies to address family time issues.

• Proceedings of the Korean Society of Embryo Transfer Conference
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• 2001.05b
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• pp.4-16
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• 2001

Sperm competent for fertilization can become capacitated, bind to the zona pellucida (ZP)of an egg in a specific manner, and complete acrosomal exocytosis. Failure to carry out these functions results in infertility. Although the interactions between the ZP and the plasma membrane overlying the sperm acrosome have been considered important for sperm-egg recognition and signalling recent results have prompted a reassessment of current paradigms concerning these interactions. In this review, we're going to discuss about the roles of the acrosomal matrix, the particulate component of the acrosomal contents, in fertilization. The general hypothesis is that acrosomal exocytosis leads to the exposure of acrosomal matrix proteins that become de facto extracellula matrix(ECM) on the surface of the sperm head, and that the dynamic interactions of this newly-exposed sperm ECM with the egg ECM (the ZP) govern sperm-egg recognition and sperm penetration of the ZP. Informations from these experiments may provide new ways to address the poor ZP binding of sperm from some human infertility patients and may offer new avenues for contraception through the disruption of purposeful sperm-ZP binding.

• The Journal of the Korea Contents Association
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• v.10 no.4
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• pp.1-9
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• 2010

Authoring tools for sketching the motion of characters to be animated have been studied. However the natural interface for sound editing has not been sufficiently studied. In this paper, I present a novel method that sound sample is selected by speaking sound-imitation words(onomatopoeia). Experiment with the method based on statistical models, which is generally used for pattern recognition, showed up to 97% in the accuracy of recognition. In addition, to address the difficulty of data collection for newly enrolled sound samples, the GLR Test based on only one sample of each sound-imitation word showed almost the same accuracy as the previous method.

• Korean Journal of Child Studies
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• v.31 no.4
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• pp.159-177
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• 2010

This study sought to identify the solutions that private-kindergarten directors use in dealing with their work-related stress. The respondents for this study were 200 kindergarten directors in Busan, Ulsan and Gyoung-Nam province. Surveys were issued and 162 were returned and were subject to statistical analysis. The survey consisted of a total of 45 questions about work-related stress and the strategies used to cope with their work situations. The data collected data were analyzed through the SPSS 12.0 program. As a result of this study, it can be argued that, firstly, in terms of the strategies to reduce work-related stress by directors, it is best to address these issues psychologically, directly and physically. Secondly, through this process, significant differences stemming from the age of directors (p < .01) were observed, while there were no significant differences in terms of educational level and management experience in these statistics. Finally, our results indicated that as a result of confirming the differences among effective plans according to total marks of the level of job stress recognition for privatekindergarten directors, there are meaningful and significant differences in the level of job stress recognition in respect to a physical effective plan (p < .05), a negative plan (p < .01) and a direct effective plan (p < .05).

• Journal of Digital Contents Society
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• v.8 no.4
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• pp.467-474
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• 2007

This paper documents the design and implementation of an automatic creating web-site tool for the blind to build their own homepage by using both voice recognition and voice mixed technology with equal ease as the non-disabled. The blind can make voice mails, schedules, address lists and bookmarks by making use of the tool. It also facilitates communication between the non-disabled with the help of their information management system. This tool converts basic commands into voice recognition, also making an offer of text-to-speech which supports voice output. In the end, the tool will remove the blind's social isolation, allowing them to enjoy the information age like the non-disabled.

• International Journal of Computer Science & Network Security
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• v.21 no.5
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• pp.256-266
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• 2021

The Convolutional Neural Network (CNN) has recently made potential improvements in face verification applications. In fact, different models based on the CNN have attained commendable progress in the classification rate using a massive amount of data in an uncontrolled environment. However, the enormous computation costs and the considerable use of storage causes a noticeable problem during training. To address these challenges, we focus on relevant data trained within the CNN model by integrating a lifting method for a better tradeoff between the data size and the computational efficiency. Our approach is characterized by the advantage that it does not need any additional space to store the features. Indeed, it makes the model much faster during the training and classification steps. The experimental results on Labeled Faces in the Wild and YouTube Faces datasets confirm that the proposed CNN framework improves performance in terms of precision. Obviously, our model deliberately designs to achieve significant speedup and reduce computational complexity in deep CNNs without any accuracy loss. Compared to the existing architectures, the proposed model achieves competitive results in face recognition tasks

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.12
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• pp.3991-4007
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• 2022

In the public healthcare, a computational system that can automatically and efficiently detect and classify falls from a video sequence has significant potential. With the advancement of deep learning, which can extract temporal and spatial information, has become more widespread. However, traditional 3D CNNs that usually adopt shallow networks cannot obtain higher recognition accuracy than deeper networks. Additionally, some experiences of neural network show that the problem of gradient explosions occurs with increasing the network layers. As a result, an enhanced three-dimensional ResNet-based method for fall detection (3D-ERes-FD) is proposed to directly extract spatio-temporal features to address these issues. In our method, a 50-layer 3D residual network is used to deepen the network for improving fall recognition accuracy. Furthermore, enhanced residual units with four convolutional layers are developed to efficiently reduce the number of parameters and increase the depth of the network. According to the experimental results, the proposed method outperformed several state-of-the-art methods.

• Journal of information and communication convergence engineering
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• v.21 no.4
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• pp.287-293
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• 2023

With the rapid development of domestic and international over-the-top markets, a large amount of video content is being created. As the volume of video content increases, consumers tend to increasingly check data concerning the videos before watching them. To address this demand, video summaries in the form of plot descriptions, thumbnails, posters, and other formats are provided to consumers. This study proposes an approach that automatically generates posters to effectively convey video content while reducing the cost of video summarization. In the automatic generation of posters, face recognition and clustering are used to gather and classify character data, and keyframes from the video are extracted to learn the overall atmosphere of the video. This study used the facial data of the characters and keyframes as training data and employed technologies such as DreamBooth, a text-to-image generation model, to automatically generate video posters. This process significantly reduces the time and cost of video-poster production.