• Journal of The Korean Association of Information Education
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• v.2 no.2
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• pp.278-285
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• 1998

Computer users frequently request large scale multimedia data such as images. voice, video rather than conventional formal data. Data in virtual fossil museum are represented as points, shape, location in multidimensional space and interrelation with other spatial object. Informations in virtual fossil museum should be maintained to manipulate spatial object and non-spatial object. In this report we propose virtual fossil museum which is consisted of two parts. In the first step, basic system is implemented in internet for non-specialist such as primary students. This system is implemented based on visual multimedia information system so that non-specialist about computer can access easily. In the second step, expert system is designed which allows computer users can store, magnify, reduce, and retrieve the spatial data. This expert system uses animation, spatial query and VRML.

• Journal of the Korea Computer Graphics Society
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• v.25 no.5
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• pp.11-20
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• 2019

With the development of deep learning technology, research is being actively carried out on user-friendly interfaces that are suitable for use in virtual reality or augmented reality applications. To support the interface using the user's hands, this paper proposes a deep learning-based fingertip detection method to enable the tracking of fingertip coordinates to select virtual objects, or to write or draw in the air. After cutting the approximate part of the corresponding fingertip object from the input image with the Grad-CAM, and perform the convolution neural network with Atrous Convolution for the cut image to detect fingertip location. This method is simpler and easier to implement than existing object detection algorithms without requiring a pre-processing for annotating objects. To verify this method we implemented an air writing application and showed that the recognition rate of 81% and the speed of 76 ms were able to write smoothly without delay in the air, making it possible to utilize the application in real time.

• Journal of the Korea Convergence Society
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• v.8 no.11
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• pp.271-277
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• 2017

In the image processing, foreground image extraction is mainly applied to recognize a moving object or an object. In the game, the objects included in the foreground image can be mainly characters, non player characters, items, and the like. These objects can be the player's primary concern with objects that are the target of players' movement, attack, defense, and collection. In this background, this research is a study to extract players' interest areas. To this end, first, the foreground image is extracted. Second, the extracted foreground image is accumulated for a certain period of time, and the image is displayed as a result image. The accumulated foreground image according to the play time helps to know the location and frequency of screen appearance of game objects. This study can help players design their interest areas and design an efficient UX/UI.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.2
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• pp.187-192
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• 2008

The Intelligent Space(ISpace) provides challenging research fields for surveillance, human-computer interfacing, networked camera conferencing, industrial monitoring or service and training applications. ISpace is the space where many intelligent devices, such as computers and sensors, are distributed. According to the cooperation of many intelligent devices, the environment, it is very important that the system knows the location information to offer the useful services. In order to achieve these goals, we present a method for representing, tracking and human Jollowing by fusing distributed multiple vision systems in ISpace, with application to pedestrian tracking in a crowd. This paper describes appearance based unknown object tracking with the distributed vision system in intelligent space. First, we discuss how object color information is obtained and how the color appearance based model is constructed from this data. Then, we discuss the global color model based on the local color information. The process of learning within global model and the experimental results are also presented.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.6
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• pp.599-607
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• 2021

Street-view images, which are omnidirectional scenes centered on a specific location on the road, can provide various obstacle information for the pedestrians. Pedestrian network data for the navigation services should reflect the up-to-date obstacle information to ensure the mobility of pedestrians, including people with disabilities. In this study, the object detection model was trained for the bollard as a major obstacle in Seoul using street-view images and a deep learning algorithm. Also, a process for updating information about the presence and number of bollards as obstacle properties for the crosswalk node through spatial matching between the detected bollards and the pedestrian nodes was proposed. The missing crosswalk information can also be updated concurrently by the proposed process. The proposed approach is appropriate for crowdsourcing data as the model trained using the street-view images can be applied to photos taken with a smartphone while walking. Through additional training with various obstacles captured in the street-view images, it is expected to enable efficient information update about obstacles on the road.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.22 no.4
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• pp.35-45
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• 2019

The objective of this study is to analyze habitat distribution on tiger, wolf, and leopard in Joseonwangjosilok. Nowaday, we only come to meet these kind of animals at the historical records because of haman-induced habitat encroachment. Historically, extinct animal became an object of game by people. So, we try to get distribution information for restoration on historical extinct animals. We made distribution map by constructing 402 counts on tiger(350), leopard(51) and wolf(1) recordsfrom 14th to Early 20th century for study. Analyzing historical materials, criteria for data analysis took into account objectivity, location information, accuracy for extinct animals. We carried out location identification of animals by using geocoding comparing with geographical name of the Joseon Dynasty period, topographic map of time under the rule of Japanese imperialism, present place name and historical materials. Database items are constructed 20 types for example appearance year of animal, population, location, damage, etc. As a result of analysis for appearance regions, tigers were recorded in capital area of higher density population intensively, and also were frequently seen at Daegu, Andong etc. Leopard and wolf were founded at regionally Gyeonggi-do and Jinju with limitation, relatively seen a few number. The reason of the appearance records like this, tiger prefer game of open and water-front area in near human residential area, there are lots of historical records such as 'Hosang'(mourning someone who killed by Tiger) and hunting. But leopard and wolf inhabit rocky area and dense forest, the reason why they made a few contact with human. Results of this are expect to be applicable restoration research for extinct animal by providing for populations, habitat environments and distribution information.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.1
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• pp.197-205
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• 2024

Development of AI and big data-based algorithms to advance and optimize the recognition and detection performance of various static/dynamic vehicles in front and around the vehicle at a time when securing driving safety is the most important point in the development and commercialization of autonomous vehicles. etc. are being studied. However, there are many research cases for recognizing the same vehicle by using the unique advantages of radar and camera, but deep learning image processing technology is not used, or only a short distance is detected as the same target due to radar performance problems. Therefore, there is a need for a convergence-based vehicle recognition method that configures a dataset that can be collected from radar equipment and camera equipment, calculates the error of the dataset, and recognizes it as the same target. In this paper, we aim to develop a technology that can link location information according to the installation location because data errors occur because it is judged as the same object depending on the installation location of the radar and CCTV (video).

• Journal of KIISE
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• v.42 no.3
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• pp.390-398
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• 2015

Spatial web objects refer to web documents that contain geographic information. Recently, services that create spatial web objects have increased greatly because of the advancements in devices such as smartphones. For services such as Twitter or Facebook, simple texts posted by users is stored along with information about the post's location. To search for such spatial web objects, a method that uses spatial information and text information simultaneously is required. Conventional spatial web object search methods mostly use R-tree and inverted file methods. However, these methods have a disadvantage of requiring a large volume of space when building indices. Furthermore, such methods are efficient for searching with many keywords but are inefficient for searching with a few keywords.. In this paper, we propose a spatial web object search method that uses a quad-tree and a patricia-trie. We show that the proposed technique is more effective than existing ones in searching with a small number of keywords. Furthermore, we show through an experiment that the space required by the proposed technique is much smaller than that required by existing ones.

• The Journal of the Korea Contents Association
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• v.13 no.8
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• pp.171-179
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• 2013

During 19th general election the customized LBSNS(Location Based SNS) application for some candidates of the National Assembly planned and developed based on the object identification, ePosition, comprising the candidate's name have been applied for an election campaign. The approval rating change before and after 19th election campaign period for each candidate was quantitatively studied how it would be affected by the candidate custom LBSNS application. Only 3 out of 24 candidates in 6 local electorates in the Daejon Metropolitan City have adopted the customized LBSNS application and the rest 21 candidates have not, whose approval rating change before and after an election campaign has been analyzed comparatively candidate by candidate. The approval rating for 3 candidates adopting LBSNS application went up by 12.6%, 11.4%, 11.2% respectively, but those for the rest 21 candidates all changed within 3%.

• The Journal of the Korea Contents Association
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• v.6 no.1
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• pp.114-125
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• 2006

Since wireless Internet services and small mobile communication devices come into wide use as well as the use of GPS is rapidly growing, researches on moving object, whose location information shifts sequently in accordance with time interval, are being carried out actively. Especially, the researches on vehicle moving object are applied to Advanced traveler information system, vehicle tracking system, and distribution transport system. These systems are very useful in searching previous positions, predicted future positions, the optimum course, and the shortest course of a vehicle by managing historical data of the vehicle movement. In addition, vehicle historical data are used for distribution transport plan and vehicle allocation. Vehicle historical data are stored at regular intervals, which can have a pattern. For example, a vehicle going repeatedly around a specific section follows a route very similar to another. If historical data of the vehicle with a repeated route course are stored at regular intervals, many redundant data occur, which result in much waste of storage. Therefore this thesis suggest a vehicle historical data store scheme for vehicles with a repeated route course using similar trajectory which efficiently store vehicle historical data.