• 제어로봇시스템학회:학술대회논문집
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• 1991.10b
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• pp.1591-1596
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• 1991

The present paper describes a method of recognizing a polyhedron employing the notion of network constraint analysis. Typical difficulties in three-dimensional object recognition, other than shading, reflection, and hidden line problems, include the case where appearances of an object vary according to observation points and the case where an object to be recognized is occluded by other objects placed in its front, resulting in incomplete information on the object shape. These difficulties can, however, be solved to a large extent, by taking account of certain local constraints defined on a polyhedral shape. The present paper assumes a model-based vision employing an appearance-oriented model of a polyhedron which is provided by placing it at the origin of a large sphere and observing it from various positions on the surface of the sphere. The model is actually represented by the sets of adjacent faces pairs of the polyhedron observed from those positions. Since the shape of a projected face gives constraint to that of its adjacent face, this results in a local constraint relation between these faces. Each projected face of an unknown polyhedron on an acquired image is examined its match with those faces in the model, producing network constraint relations between faces in the image and faces in the model. Taking adjacency of faces into consideration, these network constraint relations are analyzed. And if the analysis finally provides a solution telling existence of one to one match of the faces between the unknown polyhedron and the model, the unknown polyhedron is understood to be one of those memorized models placed in a certain posture. In the performed experiment, a polyhedron was observed from 320 regularly arranged points on a sphere to provide its appearance model and a polyhedron with arbitrarily postured, occluded, or imposed another difficulty was successfully recognized.

• Journal of the Korea Society of Computer and Information
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• v.10 no.6 s.38
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• pp.345-354
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• 2005

A mobile manipulator - a serial connection of a mobile robot and a task robot - is a very useful system to achieve various tasks in dangerous environment, because it has the higher performance than a fixed base manipulator in terms of its operational workspace size as well as efficiency. A method for estimating the position of an object in the Cartesian coordinate system based upon the geometrical relationship between the image captured by 2-DOF active camera mounted on mobile robot and the real object, is proposed. With this Position estimation, a method of determining an optimal path for the mobile manipulator from the current position to the position of object estimated by the image information using homogeneous matrices. Finally, the corresponding joint parameters to make the desired displacement are calculated to capture the object through the control of a manipulator. The effectiveness of proposed method is demonstrated by the simulation and real experiments using the mobile manipulator.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.1
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• pp.78-84
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• 2015

Depth estimation is often required for robot vision, 3D modeling, and motion control. Previous method is based on the focus measures which are calculated for a series of image by a single camera at different distance between and object. This method, however, has disadvantage of taking a long time for calculating the focus measure since the mask operation is performed for every pixel in the image. In this paper, we estimates the depth by using the focus measure of the boundary pixels located between the objects in order to minimize the depth estimate time. To detect the boundary of an object consisting of a straight line and a circle, we use the Hough transform and estimate the depth by using the focus measure. We performed various experiments for PCB images and obtained more effective depth estimation results than previous ones.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.6 no.1
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• pp.1-5
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• 2013

The number of pedestrians is considered essential information which can be used to control a person who makes a entrance or a exit into a building. The number of pedestrians, also, can be used to help to manage pedestrian traffic and the volume of pedestrian flow within the building. Due to the fact there is incorrect detection by occluded, shadows, and illumination, however, difficulty can arise in existing system which is for detection and counts of a person who makes a entrance or a exit into a building. In this paper, it is minimized that the change of illumination and the effect of shadow through the transmitted image from camera which is created and processed with great adaptability. The accuracy of the calculations can be increase as well by using Kalman Filter and Mean-Shift Algorithm in order to avoid overlapped counts. As a result of the test, it is proved that the count method that shows the accuracy of 95.4% should be effective for detection and counts.

• Journal of KIISE:Software and Applications
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• v.36 no.2
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• pp.122-130
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• 2009

Conventional approaches for car number plate detection have dealt with those input images having similar sizes and simple background acquired under well organized environment. Thus their performance get reduced when input images include number plates with different sizes and when they are acquired under different lighting conditions. To solve these problem, this paper proposes a new scheme that uses the geometrical features of number plates and their topological information with reference to other features of the car. In the first step, those edges constructing a rectangle are detected and several pixels neighboring those edges are selected as the seed pixels for region growing. For region growing, color and intensity are used as the features, and the result regions are merged to construct the candidate for a number plate if their features are within a certain boundary. Once the candidates for the number plates are generated then their topological relations with other parts of the car such as lights are tested to finally determine the number plate region. The experimental results have shown that the proposed method can be used even for detecting small size number plates where characters are not visible.

• Journal of Distribution Science
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• v.14 no.8
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• pp.153-160
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• 2016

Purpose - The current distribution enterprises have realized the necessity for integrated and specialized images in their stores. From those reasons, visual merchandising has been considered as a powerful means towards brand value judgement as well as maximizing both brand and corporate identity. This research intends to study and discuss the current situations in Korean visual merchandising and its future concept setting. Based on the research findings, this paper tries to propose the basic concept for development strategies of visual merchandising in Korean distribution market. Although the studies on visual merchandising in Korean traditional markets have been continued, visual merchandisers have been distorted by display control centers in real situations. Therefore, this study tries to set both current and future concepts in visual merchandising for further discussions and a new complement formulation. Research design, data, and methodology - This study has investigated previous studies with the way of normative study by comparing, organizing concepts and relating terms on visual merchandising. In order to be an exact research, it seems to be more appropriate to analyze this study with a deductive analysis way rather than inductive as for getting the core of visual merchandising. Besides, this study changed the term 'visual merchandising' into 'VMD', and used it as an unified one. Results - Visual merchandising has an important key in retail planning. With focusing on organizing visual merchandising concepts, it should be adequate for domestic circumstances because there are various visual merchandising concepts with different perspectives. Thus, it is necessary to establish a concept including modern and Korean features through previous studies and data. Visual merchandising can be defined as followings. It enhances the value of shop images from visual aspects and conveys brand concepts effectively. Its task is to plan and manage products sales by combining three merchandising domains such as interior, display, and merchandising. Conclusions - There are some limitations on setting academic concepts in visual merchandising due to its features as to be taken in the field focused studies. More meaningful case studies should be performed as an area of future studies. Therefore, it is necessary to perform an effectiveness analysis on empirical visual merchandising state and present the course of development.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1202-1205
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• 2005

This paper describes a method for vision-based person identification that can detect, track, and recognize person from video using multiple cues: height and dressing colors. The method does not require constrained target's pose or fully frontal face image to identify the person. First, the system, which is connected to a pan-tilt-zoom camera, detects target using motion detection and human cardboard model. The system keeps tracking the moving target while it is trying to identify whether it is a human and identify who it is among the registered persons in the database. To segment the moving target from the background scene, we employ a version of background subtraction technique and some spatial filtering. Once the target is segmented, we then align the target with the generic human cardboard model to verify whether the detected target is a human. If the target is identified as a human, the card board model is also used to segment the body parts to obtain some salient features such as head, torso, and legs. The whole body silhouette is also analyzed to obtain the target's shape information such as height and slimness. We then use these multiple cues (at present, we uses shirt color, trousers color, and body height) to recognize the target using a supervised self-organization process. We preliminary tested the system on a set of 5 subjects with multiple clothes. The recognition rate is 100% if the person is wearing the clothes that were learned before. In case a person wears new dresses the system fail to identify. This means height is not enough to classify persons. We plan to extend the work by adding more cues such as skin color, and face recognition by utilizing the zoom capability of the camera to obtain high resolution view of face; then, evaluate the system with more subjects.

• Journal of The Korean Association of Information Education
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• v.11 no.3
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• pp.299-306
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• 2007

It is urgent to have learning support for children with learning disability according to the survey made by the government educational organization. To this end, we developed a learning support system for children with learning disability. First, the system diagnoses the children with learning disability using a decision tree based on the pre-test results. Secondly, it supports for children with learning disability one of audio-, vision- and tactility-oriented learning types according to the results from the psychological learning style test. Thirdly, one-to-one study is supported for failed students at the achievement test. For the evaluation of the system, the children with disability were divided into an experimental group and a control group and the educational achievement was evaluated. We found that 10% on the average was improved in case that learning was made after the psychological test for learning styles.

• Journal of Families and Better Life
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• v.24 no.4 s.82
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• pp.51-73
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• 2006

The purpose of this study is to introduce the evolution of corporate family-friendly policies and programs, a recent business issue throughout the world. In addition, this study suggests implications for a corporate reference guide to work-family policies and programs by providing a comparative analysis of the typical stages of development of U.S. corporate family-friendly policies and programs, and by presenting model initiatives of Korean and American family-friendly companies. Just as technological changes at the time of the Industrial Revolution altered the relationship between workers and their work, more recent technological advances have again transformed this relationship, offering the promise of a society in which work demands a smaller portion of the worker's time and permitting the worker more freedom and control over work conditions. These new work arrangements have the promise of producing a new paradigm for work and family, based on which many industrialized nations have developed family-friendly policies already. Family-friendly policies and programs can be grouped into four discernable stages in the evolution of a corporate work-family agenda. According to these stages, most companies in Korea are in the predevelopment stage or stage 1. Development of scales to assess company family-friendliness is needed to create a family-friendly workplace environment, policies, and programs. It is critical that companies have champions who have the vision to step out in kent, and the determination to ensure that the family-friendly programs are solidly grounded. Companies should develop their work-family initiatives as an integral part of a program for managing diversity focusing on needs of women and minority employees.

• The Journal of Korea Robotics Society
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• v.3 no.2
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• pp.81-90
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• 2008

While increasing demand of the service for the disabled and the elderly people, assistive technologies have been developed rapidly. The natural signal of human such as voice or gesture has been applied to the system for assisting the disabled and the elderly people. As an example of such kind of human robot interface, the Soft Remote Control System has been developed by HWRS-ERC in $KAIST^[1]$. This system is a vision-based hand gesture recognition system for controlling home appliances such as television, lamp and curtain. One of the most important technologies of the system is the hand gesture recognition algorithm. The frequently occurred problems which lower the recognition rate of hand gesture are inter-person variation and intra-person variation. Intra-person variation can be handled by inducing fuzzy concept. In this paper, we propose multivariate fuzzy decision tree(MFDT) learning and classification algorithm for hand motion recognition. To recognize hand gesture of a new user, the most proper recognition model among several well trained models is selected using model selection algorithm and incrementally adapted to the user's hand gesture. For the general performance of MFDT as a classifier, we show classification rate using the benchmark data of the UCI repository. For the performance of hand gesture recognition, we tested using hand gesture data which is collected from 10 people for 15 days. The experimental results show that the classification and user adaptation performance of proposed algorithm is better than general fuzzy decision tree.