• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.6A
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• pp.497-502
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• 2012

In this paper, we present an immersive videoconferencing system that enables gaze correction between users in the internet protocol TV (IPTV) environment. The proposed system synthesizes the gaze corrected images using the depth estimation and the virtual view synthesis algorithms as one of the most important techniques of 3D video system. The conventional processes, however, causes several problems, especially temporal inconsistency of a depth video. This problem leads to flickering artifacts discomforting viewers. Therefore, in order to reduce the temporal inconsistency problem, we exploit the joint bilateral filter which is extended to the temporal domain. In addition, we apply an outlier reduction operation in the temporal domain. From experimental results, we have verified that the proposed system is sufficient to generate the natural gaze-corrected image and realize immersive videoconferencing.

• Journal of Korea Multimedia Society
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• v.25 no.2
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• pp.145-156
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• 2022

Nowadays, the complexity of object tracking models among hardware applications has become a more in-demand duty to complete in various indeterminable environment tracking situations with multifunctional algorithm skills. In this paper, we propose a virtual city environment using AirSim (Aerial Informatics and Robotics Simulation - AirSim, CityEnvironment) and use the DQN (Deep Q-Learning) model of deep reinforcement learning model in the virtual environment. The proposed object tracking DQN network observes the environment using a deep reinforcement learning model that receives continuous images taken by a virtual environment simulation system as input to control the operation of a virtual drone. The deep reinforcement learning model is pre-trained using various existing continuous image sets. Since the existing various continuous image sets are image data of real environments and objects, it is implemented in 3D to track virtual environments and moving objects in them.

• Journal of the Society of Disaster Information
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• v.16 no.1
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• pp.96-110
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• 2020

Recently, due to global warming, it is easily exposed to various disasters such as fire, flood, and earthquake. In particular, large-scale disasters have continuously been occurring in crowded areas such as traditional markets, facilities for the elderly and children, and public facilities where various people stay. Purpose: This study aims to detect a fire occurred in crowded facilities early in the event to analyze and provide an optimal evacuation route using big data and advanced technology. Method: The researchers propose a new algorithm through context-aware 3D object model technology and A* algorithm optimization and propose a scenario-based optimal evacuation route selection technique. Result: Using the HPA* E algorithm, the evacuation simulation in the event of a fire was reproduced as a 3D model and the optimal evacuation route and evacuation time were calculated for each scenario. Conclusion: It is expected to reduce fatalities and injuries through the evacuation induction technique that enables evacuation of the building in the shortest path by analyzing in real-time via fire detection sensors that detects the temperature, flame, and smoke.

• Journal of Broadcast Engineering
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• v.14 no.3
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• pp.366-377
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• 2009

In this paper, we implement the real-time system which extracts 3-dimensional coordinates from right and left images captured by a stereo camera and provides users with reality through a virtual space operated by the 3-dimensional coordinates. In general, all pixels in correspondence region are compared for the disparity estimation. However, for a real time process, the central coordinates of the correspondence region are only used in the proposed algorithm. In the implemented system, 3D coordinates are obtained by using the depth information derived from the estimated disparity and we set user's hand as a region of interest(ROI). After user's hand is detected as the ROI, the system keeps tracking a hand's movement and generates a virtual space that is controled by the hand. Experimental results show that the implemented system could estimate the disparity in real -time and gave the mean-error less than 0.68cm within a range of distance, 1.5m. Also It had more than 90% accuracy in the hand recognition.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.3
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• pp.229-240
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• 2012

In Korea, u-City has been constructed as IT-based new city with introduction of the ubiquitous concept. However, most currently provided u-services are just monitoring services based on the USN(Ubiquitous Sensor Network) technology, so spatial analysis is insufficient. Especially, buildings have been rapidly constructed and expanded in multi-levels, and people spend a lot of time in indoor space, so indoor spatial analysis is necessary. Therefore, connectivity relationship in indoor space is analyzed using the topological data model. Topological relationships could be redefined due to the dynamic changes of environment in indoor space, and changes could have an effect on analysis results. In this paper, the algorithms of finding isolated zones is developed by analyzing connectivity relationship between space objects in built-environments after changes of environment in indoor space due to specific situation such as fire. And the system that visualizes isolated zones as well as three-dimensional data structure of indoor space is developed to get the analysis result by using the analysis algorithms.

• Proceedings of the Korean Information Science Society Conference
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• 2010.06b
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• pp.289-293
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• 2010

21C 현대 문명사회에서는 도시의 고밀도 및 팽창으로 인하여 도시 내 생태계가 파괴되면서 생물서식처의 환경 악화 및 엄청난 감소가 초래되었으며, 그 결과로 인하여 인간과 생물이 접촉할 수 있는 공간이 현저하게 줄어들고 있다. 또한 도시 영역의 확장을 위하여 산림 및 녹지의 감소, 녹지의 분절 및 단절화, 해안 매립 등이 계획 없이 무분별하게 진행됨으로써, 각종 동식물의 개체 수 감소 및 토양의 건조화 등이 발생하고 있으며, 그 영향으로 생물종의 다양성이 떨어지고, 도시 생태계의 교란이 심해지고 있다. 이러한 도시 생태계의 교란은 도시에 거주하고 있는 시민들의 생활의 질이 떨어지게 하고 많은 환경 문제들의 주원인이 되고 있다. 지속적이면서도 자연친화적인 도시발전을 위해서는 도시 내 자연생태계를 회복하고 생물서식공간을 종합적으로 보전하면서 복원해야 한다는 요구가 높아지고 있지만, 이를 체계적으로 이루기 위한 방법론의 부재에 시달리고 있었다. 이러한 가운데 유럽을 중심으로 생겨난 비오톱(Biotope)과 비오톱 지도화 방법이 생태계를 보전하며, 시민들에게 다양한 자연체험과 휴양 기회를 제공하고 친환경적인 도시계획을 위한 핵심적인 역할을 하는 것으로 인식되고 있다. 하지만, 기존의 비오톱 지도는 이미지 기반의 2차원 지도로 제공되고 있어, 거리 및 공간 분석에 취약하고 정보전달력이 부족하여, 익숙한 전문가가 아닌 경우 비오톱을 이해하는데 상당한 정도의 시간이 필요하였다. 이에 본 논문에서는 공간정보가 결여된 2차원 형태의 GIS 데이터를 기반으로 3차원 공간 데이터를 자동으로 생성하고, 위성영상과 DEM(Digital Elevation Model)을 이용하여 3차원 지형을 만들어 각 주제도별로 입체적인 분석이 가능하도록 하였다. 또한 동영상 녹화 기능과 3차원 객체 추가 기능을 이용하여, 자연생태계를 고려한 도시의 설계를 진행하는 경우 3차원적인 모델링을 제공함으로써 효과적이면서도 사용자의 이해도를 향상 시킬 수 있는 정보 전달력을 가질 수 있도록 설계 및 구현하였다.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.6
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• pp.48-60
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• 2011

Nowadays, the 3D community is actively researching on 3D imaging and free-viewpoint video (FVV). The free-viewpoint rendering in multi-view video, virtually move through the scenes in order to create different viewpoints, has become a popular topic in 3D research that can lead to various applications. However, there are restrictions of cost-effectiveness and occupying large bandwidth in video transmission. An alternative to solve this problem is to generate virtual views using a single texture image and a corresponding depth image. A critical issue on generating virtual views is that the regions occluded by the foreground (FG) objects in the original views may become visible in the synthesized views. Filling this disocclusions (holes) in a visually plausible manner determines the quality of synthesis results. In this paper, a new approach for handling disocclusions using depth based inpainting algorithm in synthesized views is presented. Patch based non-parametric texture synthesis which shows excellent performance has two critical elements: determining where to fill first and determining what patch to be copied. In this work, a noise-robust filling priority using the structure tensor of Hessian matrix is proposed. Moreover, a patch matching algorithm excluding foreground region using depth map and considering epipolar line is proposed. Superiority of the proposed method over the existing methods is proved by comparing the experimental results.

• Journal of Korea Game Society
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• v.6 no.2
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• pp.3-12
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• 2006

Recently, Many 3D augmented reality games that provide strengthened immersive have appeared in the 3D game environment. In this article, we describe a barehanded interaction method based on human hand gestures for augmented reality games. First, feature points are extracted from input video streams. Point features are tracked and motion of moving objects are computed. The shape of the motion trajectories are used to determine whether the motion is intended gestures. A long smooth trajectory toward one of virtual objects or menus is classified as an intended gesture and the corresponding action is invoked. To prove the validity of the proposed method, we implemented two simple augmented reality applications: a gesture-based music player and a virtual basketball game. In the music player, several menu icons are displayed on the top of the screen and an user can activate a menu by hand gestures. In the virtual basketball game, a virtual ball is bouncing in a virtual cube space and the real video stream is shown in the background. An user can hit the virtual ball with his hand gestures. From the experiments for three untrained users, it is shown that the accuracy of menu activation according to the intended gestures is 94% for normal speed gestures and 84% for fast and abrupt gestures.

• International Journal of Highway Engineering
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• v.13 no.3
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• pp.111-119
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• 2011

The noise prediction model, KRON-2006, in South Korea has been developed for obtaining the average noise level. The model is based on an outdoor sound propagation method based on ISO9613 and ASJ Model-1998 and supports the analysis of the linear noise source, such as highway, for obtaining Leq. Because of that, the model can't obtain Lmax, Lmin from the time series noise profile based on traffic at every moment. In order to address this problem, the real time noise prediction model based on traffic simulation using GIS model and algorithm is proposed. It can predict the vehicle point noise level based on vehicle type, speed generated from traffic simulation by using headway and obtain Lmax, Lmin as integrating the noise profile generated from it at every moment. An evalution of the noise prediciton model using field measurements finds good agreement between predicted and measured noise levels at 1m, 8m, 15m from curb of the near side lane.

• The KIPS Transactions:PartD
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• v.8D no.3
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• pp.203-210
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• 2001

These days data is being collected and accumulated in a wide variety of fields. Stored data itself is to be an information system which helps us to make decisions. An information system includes many kinds of necessary and unnecessary attribute. So many algorithms have been developed for finding useful patterns from the data and reasoning approximately new objects. We are interested in the simple and understandable rules that can represent useful patterns. In this paper we propose an algorithm which can reduce the information in the system to a minimum, based on a probabilistic rough set theory. The proposed algorithm uses a value that tolerates accuracy of classification. The tolerant value helps minimizing the necessary attribute which is needed to reason a new object by reducing conditional attributes. It has the advantage that it reduces the time of generalizing rules. We experiment a proposed algorithm with the IRIS data and Wisconsin Breast Cancer data. The experiment results show that this algorithm retrieves a small reduct, and minimizes the size of the rule under the tolerant classification rate.