• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.6
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• pp.608-616
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• 2001

This paper proposes a face recognition technique that effectively combines fixed graph matching (FGM) and Fisherface algorithm. EGM as one of dynamic link architecture uses not only face-shape but also the gray information of image, and Fisherface algorithm as a class specific method is robust about variations such as lighting direction and facial expression. In the proposed face recognition adopting the above two methods, linear projection per node of an image graph reduces dimensionality of labeled graph vector and provides a feature space to be used effectively for the classification. In comparison with a conventional EGM, the proposed approach could obtain satisfactory results in the perspectives of recognition speeds. Especially, we could get higher average recognition rate of 90.1% than the conventional methods by hold-out method for the experiments with the Yale Face Databases and Olivetti Research Laboratory (ORL) Databases.

• Journal of Intelligence and Information Systems
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• v.14 no.4
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• pp.201-216
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• 2008

Nowadays various new items are available, but limitation of searching effort makes it difficult for customers to search new items which they want to purchase. Therefore new item providers and customers need recommendation systems which recommend right items for right customers. In this research, we focus on the new item recommendation issue, and suggest preference boundary- based procedures which extend traditional content-based algorithm. We introduce the concept of preference boundary in a feature space to recommend new items. To find the preference boundary of a target customer, we suggest heuristic algorithms to find the centroid and the radius of preference boundary. To evaluate the performance of suggested procedures, we have conducted several experiments using real mobile transaction data and analyzed their results. Some discussions about our experimental results are also given with a further research area.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.10a
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• pp.481-484
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• 2012

Information subject in the revision educational curriculum actually devoted a good deal of space to increase problem-solving ability through programming learning. However, it is not easy for learners to be immersed in the programming teaching by using only computers, which leads to the heavy logical burden in learning. Therefore, many studies are being carried out on the programming teaching by using robots. Moreover, smartphones have been rapidly widespread in the past few years; as a result, the present immersion situation in smartphones and the side effect problems are on the rise. This study tried to develop a programming teaching model to have a significant synergy effect in programming teaching by using robots with the immersion effect in smartphones. This paper attempts to improve programming teaching effectively by introducing the special feature of smartphones: the immersion greatly needed to programming teaching.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.10a
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• pp.903-905
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• 2012

Recent research on Augmented Reality is Actively expand and Augmented reality feature added to the social network system (Social Network System) has become a necessity. In this paper, GPS-based Augmented Reality System for Social Network is introduced, is proposed. This system can add recent check-in friends in facebook by automatically to synchronizing the location coordinate, and it could also adding location coordinates system is represented in a real-world environment by AR, is Marker-based AR system that was Commonly used AR system is a huge cost by handheld devices in processing and storage space, the disadvantages of the marker-based AR systems can be solved by using Location-based AR applications. Therefore, the proposed GPS-based Augmented Reality System for Social Network, automatically searches for the optimal speed for Wifi and 4G network to iOS Hand AR system was desired in future.

• The KIPS Transactions:PartB
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• v.10B no.2
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• pp.179-188
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• 2003

In content-based image retrieval, the query is an image itself and the retrieval process is the process that seeking the similar images to the given query image. In this way of retrieval, the user has to know the basic physical features of target images that he wants to retrieve. But it has some restriction because to retrieve the target image he has to know the basic physical feature space such as color, texture, shape and spatial relationship. In this paper, we propose an emotion-based retrieval system. It uses the emotion that color images have. It is different from past emotion-based image retrieval in point of view that it uses relevance feedback to estimate the users intend and it is easily combined with past content-based image retrieval system. To test the performance of our proposed system, we use MPEG-7 color descriptor and emotion language such as "warm", "clean", "bright" and "delight" We test about 1500 wallpaper images and get successful result.lpaper images and get successful result.

• KIEAE Journal
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• v.7 no.1
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• pp.5-13
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• 2007

Since aging has become one of most hot and serious issues in the whole global world, universal design as a strategic concept to enable the elderly age in place has received much attention and its importance is getting recognized. Japan has undergone the Aging phenomenon much earlier than Korea and other countries. During that time, through much trials and errors, it accumulated the wisdoms and techniques to precede aging friendly environment and products. Therefore current Japan house is a comprehensive setting which embraces lots of universal design features that has a valuable implication for Korean development that faces fast aging future. The purpose of this study was to delineate characteristics of universal design features appeared in Japanese Model houses. One site of housing park in the city where various model houses of representative housing construction companies was selected as a cluster area for data collecting. Data were collected mainly through field survey at the housing park of Tokyo during November, 2006, and additional data were collected through website and company information of relevant company. Universal design features were extracted for 17 houses of the housing park and sorted and analyzed according to the analysis frame. The frame were made using 2 major clusters; space area, and 8 universal design principle. Results showed a range of universal design feature and its detail universal design principle satisfied. The 8 principle currently developed became to house realistic practical examples and theory became proved its impractical power. The academic, educational and industrial implication were documented.

• Journal of KIISE:Databases
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• v.30 no.2
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• pp.176-183
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• 2003

Various techniques including histograms, sampling and parametric techniques have been proposed to estimate query result sizes for the query optimization. Histogram-based techniques are the most widely used form for the selectivity estimation in relational database systems. However, in the spatio-temporal databases for the moving objects, the continual changes of the data distribution suffer the direct utilization of the state of the art histogram techniques. Specifically for the future queries, we need another methodology that considers the updated information and keeps the accuracy of the result. In this paper we propose a novel approach based upon the duality and the marginal distribution to construct a histogram with very little time since the spatio-temporal histogram requires the data distribution defined by query predicates. We use data synopsis method in the dual space to construct spatio-temporal histograms. Our method is robust to changing data distributions during a certain period of time while the objects keep the linear movements. An additional feature of our approach supports the dynamic update incrementally and maintains the accuracy of the estimated result.

• The KIPS Transactions:PartB
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• v.14B no.4
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• pp.303-310
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• 2007

In machine learning, the ensemble classifier that is a set of classifiers have been introduced for higher accuracy than individual classifiers. We propose a new ensemble learning method that employs a set of region based classifiers. To show the performance of the proposed method. we compared its performance with that of bagging and boosting, which ard existing ensemble methods. Since the distribution of data can be different in different regions in the feature space, we split the data and generate classifiers based on each region and apply a weighted voting among the classifiers. We used 11 data sets from the UCI Machine Learning Repository to compare the performance of our new ensemble method with that of individual classifiers as well as existing ensemble methods such as bagging and boosting. As a result, we found that our method produced improved performance, particularly when the base learner is Naive Bayes or SVM.

• Journal of Computing Science and Engineering
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• v.6 no.1
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• pp.1-11
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• 2012

Computed tomography (CT) images are widely used for the analysis of the temporal evaluation or monitoring of the progression of a disease. The follow-up examinations of CT scan images of the same patient require a 3D registration technique. In this paper, an automatic and robust registration is proposed for the rigid registration of 3D CT images. The proposed method involves two steps. Firstly, the two CT volumes are aligned based on their principal axes, and then, the alignment from the previous step is refined by the optimization of the similarity score of the image's voxel. Normalized cross correlation (NCC) is used as a similarity metric and a downhill simplex method is employed to find out the optimal score. The performance of the algorithm is evaluated on phantom images and knee synthetic CT images. By the extraction of the initial transformation parameters with principal axis of the binary volumes, the searching space to find out the parameters is reduced in the optimization step. Thus, the overall registration time is algorithmically decreased without the deterioration of the accuracy. The preliminary experimental results of the study demonstrate that the proposed method can be applied to rigid registration problems of real patient images.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.6
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• pp.565-570
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• 2013

The mirror neuron regions which are distributed in cortical area handled a functionality of intention recognition on the basis of imitative learning of an observed action which is acquired from visual-information of a goal-directed action. In this paper an automated intention recognition system is proposed by applying computational model of mirror neuron system to the human-robot interaction system. The computational model of mirror neuron system is designed by using dynamic neural networks which have model input which includes sequential feature vector set from the behaviors from the target object and actor and produce results as a form of motor data which can be used to perform the corresponding intentional action through the imitative learning and estimation procedures of the proposed computational model. The intention recognition framework is designed by a system which has a model input from KINECT sensor and has a model output by calculating the corresponding motor data within a virtual robot simulation environment on the basis of intention-related scenario with the limited experimental space and specified target object.