• Journal of the Korea Society of Computer and Information
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• v.15 no.2
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• pp.47-53
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• 2010

This paper proposed Residual Image detection and Color Info using the face detection technique. The proposed technique was fast processing speed and high rate of face detection on the video. In addition, this technique is to detection error rate reduced through the calibration tasks for tilted face image. The first process is to extract target image from the transmitted video images. Next, extracted image processed by window rotated algorithm for detection of tilted face image. Feature extraction for face detection was used for AdaBoost algorithm.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.267-268
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• 2006

Advanced TV makes the life more convenient for the viewers and it is based on the recognition technology. In this paper, we propose the implementation of face tracking system for efficient face recognition in intelligent digital TV. To recognize the face, face detection should be performed earlier. We use the motion information to track the face. Continuous face tracking is possible by using continuous detected face region and motion information. Thus the computational complexity of the recognition module in the whole system can be reduced.

• Journal of Information Processing Systems
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• v.11 no.4
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• pp.643-654
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• 2015

Face recognition under controlled settings, such as limited viewpoint and illumination change, can achieve good performance nowadays. However, real world application for face recognition is still challenging. In this paper, we propose using the combination of Affine Scale Invariant Feature Transform (SIFT) and Probabilistic Similarity for face recognition under a large viewpoint change. Affine SIFT is an extension of SIFT algorithm to detect affine invariant local descriptors. Affine SIFT generates a series of different viewpoints using affine transformation. In this way, it allows for a viewpoint difference between the gallery face and probe face. However, the human face is not planar as it contains significant 3D depth. Affine SIFT does not work well for significant change in pose. To complement this, we combined it with probabilistic similarity, which gets the log likelihood between the probe and gallery face based on sum of squared difference (SSD) distribution in an offline learning process. Our experiment results show that our framework achieves impressive better recognition accuracy than other algorithms compared on the FERET database.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.7
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• pp.2667-2682
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• 2015

Due to the wide application of face recognition (FR) in information security, surveillance, access control and others, it has received significantly increased attention from both the academic and industrial communities during the past several decades. However, partial face occlusion is one of the most challenging problems in face recognition issue. In this paper, a novel method based on linear regression-based classification (LRC) algorithm is proposed to address this problem. After all images are downsampled and divided into several blocks, we exploit the evaluator of each block to determine the clear blocks of the test face image by using linear regression technique. Then, the remained uncontaminated blocks are utilized to partial occluded face recognition issue. Furthermore, an improved Distance-based Evidence Fusion approach is proposed to decide in favor of the class with average value of corresponding minimum distance. Since this occlusion removing process uses a simple linear regression approach, the completely computational cost approximately equals to LRC and much lower than sparse representation-based classification (SRC) and extended-SRC (eSRC). Based on the experimental results on both AR face database and extended Yale B face database, it demonstrates the effectiveness of the proposed method on issue of partial occluded face recognition and the performance is satisfactory. Through the comparison with the conventional methods (eigenface+NN, fisherfaces+NN) and the state-of-the-art methods (LRC, SRC and eSRC), the proposed method shows better performance and robustness.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.32 no.2
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• pp.124-134
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• 2024

This study is based on the Expectation Confirmation Theory (ECT) and categorizes trust types in non-face-to-face boarding services into three dimensions: structural assurance, platform, and service provider. It analyzes the impact of these trust types on users' perceived usefulness, satisfaction, and continuous usage intentions. Using a structural equation model, the study found that the three dimensions of trust positively influence users' satisfaction and perception of usefulness, thereby promoting intentions for continuous use. However, perceived risk weakens the positive relationship between trust and continuous usage intentions. By exploring the moderating role of perceived risk in non-face-to-face boarding services, this study analyzes its impact on user behavior patterns, contributing to the optimization of service design and enhancement of user trust. This study promotes widespread acceptance and continuous use of the service, and is crucial for developing effective non-contact service strategies that meet the needs and expectations of Chinese travelers in the post-pandemic travel environment. The findings provide a new perspective and empirical evidence for understanding user attitudes and behaviors towards non-face-to-face services, holding significant theoretical and practical implications.

• Asian Journal for Public Opinion Research
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• v.9 no.2
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• pp.188-211
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• 2021

Decreasing response rates to traditional survey methods, like face-to-face and telephone interviews, have led survey practitioners around the world to seek new ways of conducting surveys in recent years." The COVID-19 pandemic exacerbated this problem because it made conducting face-to-face interviews even more difficult than before. For example, it made conducting face-to-face surveys infeasible in 2020 in South Korea, and so the Korean Academic Multimode Open Survey (KAMOS) was unable to conduct a planned face-to-face survey to recruit new panel members. The entire 8,514-member panel, established via two-stage probability-based sampling from 2016 to 2019, was invited to take three online/telephone surveys in 2020. Of these panel members, 1,352 responded to at least one survey in 2020. To test to what extent the panel remained representative of the adult South Korean population, we compared the two groups of panel members: those who responded to at least one survey in 2020 and those who did not. After weighting both groups on the basis of age, sex, and geographical area, we analyzed their responses to some of the questions that were asked during multiple rounds of the face-to-face panel-recruiting interviews. Using Cohen's d for survey items that could be analyzed numerically and Cramér's V for categorical items, we were able to conclude that the respondents to the 2020 surveys were equivalent to the non-respondents in terms of both demographics and in the answers they originally gave to substantive questions on a variety of topics related to social science or public opinion research, including questions about quality of life, societal issue, and politics (Cohen's d items <0.2, 95% CI; Cramér's V items <0.1, 95% CI). This analysis may provide a model for others who wish to test the continued representativeness of their panel or who would like to use a different survey mode or change some other aspect of their methodology and test whether it is equivalent to their former methodology. Our success in building a panel that retained its representativeness may be useful to those in other countries where face-to-face surveys had previously been the norm but are becoming increasingly difficult to conduct.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1244-1248
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• 2005

In this paper, we propose fuzzy c-means (FCM) to solve recognition errors in invariant range image, multi-pose face recognition. Scale, center and pose error problems were solved using geometric transformation. Range image face data was digitized into range image data by using the laser range finder that does not depend on the ambient light source. Then, the digitized range image face data is used as a model to generate multi-pose data. Each pose data size was reduced by linear reduction into the database. The reduced range image face data was transformed to the gradient face model for facial feature image extraction and also for matching using the fuzzy membership adjusted by fuzzy c-means. The proposed method was tested using facial range images from 40 people with normal facial expressions. The output of the detection and recognition system has to be accurate to about 93 percent. Simultaneously, the system must be robust enough to overcome typical image-acquisition problems such as noise, vertical rotated face and range resolution.

• Journal of the Korean Applied Science and Technology
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• v.40 no.1
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• pp.146-159
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• 2023

As a makeup technique for a baby-faced image, there will be a difference in perception of the expression technique of baby-faced makeup according to general matters.' Two hypotheses were supported: 'There will be a difference in perception of the expression technique of baby face makeup depending on the general characteristics', and the makeup technique for creating a baby face image is an important function for both men and women, as well as appearance. As a 'physical resource' for social activities, it was confirmed that there is an improvement in the efficiency of the body and mind and an outstanding improvement in mental ability in daily life. Through the results of the study on 'expression of baby face image makeup', awareness and interest in baby face images are high, but research on the production of baby face images is needed. The need for facial expression elements for baby face makeup is expected to be used as basic data for developing baby face images, and this study focuses on external face management for baby face images and baby face makeup.

• Proceedings of the Korean Geotechical Society Conference
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• 2010.09b
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• pp.200-211
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• 2010

Tunnel Mapper, which is tunnel face survey system was used to conduct Face Mapping on the face of the tunnel that is under construction. Then, accuracy and utility value on the forecast of discontinuity were verified to verify the field application in order to present the measures for the use of the system for conducting research on the discontinuity. As result of the directivity verification following discontinuity‘s project, forecasted measurement and actually researched measurement error for the Dip direction and Dip angle was less than ${\pm}10$. Accuracy was 82.6% for Dip direction and 90.7% for Dip angle, which are high. Accordingly, face research discontinuity forecasting system's reliability level towards directivity is high. Tunnel Mapper, a tunnel face survey system can be leveraged to replace face's visual survey and to obtain objective information, enabling execution of the survey system that can automate face survey going beyond time and space related limitations.

• 한국정보디스플레이학회:학술대회논문집
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• 2007.08a
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• pp.617-620
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• 2007

The temporal dark image sticking phenomena for both the face-to-face and coplanar sustain electrode structures were compared. For both structures, the temporal dark image sticking phenomena were examined by measuring the difference in the IR emission, display luminance, perceived luminance, and temperature between the image sticking and the no image sticking cells. For the face-to-face structure, the 10-min sustain discharge causes a small increment of the panel temperature thanks to the ITO-less electrode structure, thereby resulting in mitigating the temporal dark image sticking phenomenon.