• 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.

• Journal of Korea Multimedia Society
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• v.7 no.12
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• pp.1692-1699
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• 2004

Many researchers have developed various techniques for detection of human faces in ordinary still images. Face detection is the first imperative step of human face recognition systems. The two main problems of human face detection are how to cutoff the running time and how to reduce the number of false positives. In this paper, we present frontal and near-frontal face detection algorithm in still gray images using a thick edge image and neural network. We have devised a new filter that gets the thick edge image. Our overall scheme for face detection consists of two main phases. In the first phase we describe how to create the thick edge image using the filter and search for face candidates using a whole face detector. It is very helpful in removing plenty of windows with non-faces. The second phase verifies for detecting human faces using component-based eye detectors and the whole face detector. The experimental results show that our algorithm can reduce the running time and the number of false positives.

• Journal of the Korea Society of Computer and Information
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• v.8 no.2
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• pp.31-36
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• 2003

This paper proposes an acceleration method of PCA(Principal Component Analysis) based feature detection. The feature detection method makes decision whether the target feature is included in a given image, and if included, calculates the position and extent of the target feature. The position and scale of the target feature or face is not known previously, all the possible locations should be tested for various scales to detect the target. This is a search Problem in huge search space. This Paper proposes a fast face and feature detection method by reducing the search space using the multi-stage prediction map and contour Prediction map. A Proposed method compared to the existing whole search way, and it was able to reduce a computational complexity below 10％ by experiment.

• Journal of KIISE:Software and Applications
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• v.27 no.2
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• pp.193-200
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• 2000

The extraction of face regions is required for Head Gesture Interface which is a natural user interface. Recently, many researchers are interested in using color information to detect face regions in image sequences. Two most widely used color models, HSI color model and YIQ color model, were selected for this study. Actually H-component of HSI and I-component of YIQ are used in this research. Given the difference in the color component, this study was aimed to compare the performance of face region detection between the two models. First, we search the optimum range of facial color for each color component, examining the detection accuracy of facial color regions for variant threshold range about facial color. And then, we compare the accuracy of the face box for both color models by using optimal facial color and motion information. As a result, a range of $0^{\circ}{\sim}14^{\circ}$ in the H-component and a range of $-22^{\circ}{\sim}-2^{\circ}$ in the I-component appeared to be the most optimum range for extracting face regions. When the optimal facial color range is used, I-component is better than H-component by about 10% in accuracy to extract face regions. While optimal facial color and motion information are both used, I-component is also better by about 3% in accuracy to extract face regions.

• The KIPS Transactions:PartB
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• v.9B no.6
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• pp.853-862
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• 2002

Face Detection can be defined as follows : Given a digitalized arbitrary or image sequence, the goal of face detection is to determine whether or not there is any human face in the image, and if present, return its location, direction, size, and so on. This technique is based on many applications such face recognition facial expression, head gesture and so on, and is one of important qualify factors. But face in an given image is considerably difficult because facial expression, pose, facial size, light conditions and so on change the overall appearance of faces, thereby making it difficult to detect them rapidly and exactly. Therefore, this paper proposes fast and exact face detection which overcomes some restrictions by using neural network. The proposed system can be face detection irrelevant to facial expression, background and pose rapidily. For this. face detection is performed by neural network and detection response time is shortened by reducing search region and decreasing calculation time of neural network. Reduced search region is accomplished by using skin color segment and frame difference. And neural network calculation time is decreased by reducing input vector sire of neural network. Principle Component Analysis (PCA) can reduce the dimension of data. Also, pose estimates in extracted facial image and eye region is located. This result enables to us more informations about face. The experiment measured success rate and process time using the Squared Mahalanobis distance. Both of still images and sequence images was experimented and in case of skin color segment, the result shows different success rate whether or not camera setting. Pose estimation experiments was carried out under same conditions and existence or nonexistence glasses shows different result in eye region detection. The experiment results show satisfactory detection rate and process time for real time system.

• Journal of KIISE:Software and Applications
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• v.31 no.2
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• pp.213-223
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• 2004

In this paper, we propose a new face detection method for real-time applications. It is based on the template-matching and appearance-based method. At first, we apply Min-max normalization with histogram equalization to the input image according to the variation of intensity. By applying the PCA transform to both the input image and template, PC components are obtained and they are applied to the LDA transform. Then, we estimate the distances between the input image and template, and we select one region which has the smallest distance. SVM is used for final decision whether the candidate face region is a real face or not. Since we detect a face region not the full region but within the $\pm$12 search window, our method shows a good speed and detection rate. Through the experiments with 6 category input videos, our algorithm shows the better performance than the existing methods that use only the PCA transform. and the PCA and LDA transform.

• Journal of Sensor Science and Technology
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• v.8 no.1
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• pp.63-68
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• 1999

We proposed a method of eye pattern detection in the 2-D image which was obtained by CCD video camera. To detect face region and eye pattern, we proposed pattern search network and batch SVD algorithm which had the statistical equivalence of PCA. We also used HMM to improve the accuracy of detection. As a result, we acknowledged that the proposed algorithm was superior to PCA pattern detection algorithm in computational cost and accuracy of defection. Furthermore, we evaluated that the proposed algorithm was possible in real-time face pattern detection with 2 frame images per second.

• International Journal of Advanced Culture Technology
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• v.12 no.3
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• pp.449-465
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• 2024

This study conducted a systematic literature review using online databases to investigate the effective feedback types that enhance the learning experiences of online students. Feedback is a critical component for learner success. With the expansion of online education, the importance of feedback has become more evident due to the reduced interaction between instructors and learners. Instructors must provide high-quality feedback that motivates learners and supports their educational goals. This involves using automated tools appropriate for the environment and effective feedback strategies to deliver personalized feedback. The literature was gathered through an extensive search process, adhering to predetermined inclusion and exclusion criteria, and included a risk assessment of selected studies, drawing from sources such as Google Scholar, Elsevier, and other Scopus-indexed journals. The review adhered to the guidelines set forth by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Specific keywords related to the study's focus, including "Online learning," "Improving learning," "Learner performance," "Feedback type," and "Feedback," guided the database searches. The protocol for selecting systematic reviews on learning enhancement involved screening articles published from 2013 to 2021 based on their titles and abstracts according to established criteria. Analyzing and studying data on learning patterns in non-face-to-face educational environments can improve learners' needs and educational effectiveness. Selecting the right types of feedback, taking into account the learners' levels and educational objectives, is crucial for providing effective feedback. A variety of feedback types are essential for the continuous improvement of learners' learning.

• Journal of Software Engineering Society
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• v.23 no.4
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• pp.151-163
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• 2010

In the defense software domain where large-scale software products in various application areas need to be built, reusing software is regarded as one of the important practices to build software products efficiently and economically. There have been many efforts to apply various methods to support software reuse in the defense software domain. However, developers in the defense software domain still experience many difficulties and face obstacles in reusing software assets. In this paper, we analyze practical problems of software reuse in the defense software domain, and define core requirements to solve those problems. To meet these requirements, we are currently developing the Component Grid system, a reuse-support system that provides a developer-centric software reuse environment. We have designed an architecture of Component Grid, and defined essential elements of the architecture. We have also developed the core approaches for developing the Component Grid system: a semantic-tagging-based requirement tracing method, a reuse-knowledge representation model, a social-network-based asset search method, a web-based asset management environment, and a wiki-based collaborative and participative knowledge construction and refinement method. We expect that the Component Grid system will contribute to increase the reusability of software assets in the defense software domain by providing the environment that supports transparent and efficient sharing and reuse of software assets.

• Journal of English Language & Literature
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• v.56 no.2
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• pp.301-328
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• 2010

Many recent British novels engage with the construction and deconstruction of history and identity; and in dealing with these historical, or historicised novels it seems to be an untouchable ground that truth is beyond grasp. Even when approached, its authenticity should be examined under the post-modern "incredulity toward metanarrative" discourses. Julian Barnes's 1998 novel England, England may be one of these. Yet, unlike others it achieves a complicated and controversial status as a new kind of historiographic metafiction by providing selfconscious reflections on the invention of innocence and the questionable notion of historical authenticity against the background of current postmodern historical, cultural, and literary explorations. The book, set in a near-future, namely post-post-modern England, starts with a story of a young girl, Martha Cochrane, whose first memory goes back to her early infantile years. Yet, the narrator comments that it is a lie, "her first artfully, innocently arranged lie," since memory, or history, is a product of identity, and vice versa. Her memory of the jigsaw puzzle is both a reminiscent and a significant component of who she is now, both a simulacrum and the original of herself. The correlation between her individual memory and identity parallels that of a region, England, in formation of its history and nationality. "England, England" is the replicated miniature of the former glorious Kingdom as well as a becoming der Ding an sich (the thing itself). In search of the English history and identity, the author satirizes the modern mind's perception of the unreliability and arbitrariness of memory and history, and further explores the alternative to the postmodern discourses by suggesting the probability of inventing innocence glimpsed in children's face "believing while disbelieving." In doing so, the author reconstructs not only the history of Englishness on the ground where nothing seems to be solid, but more importantly also the postmodern theme of relativity in relation to memory, history and identity.