• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.6
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• pp.1355-1360
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• 2014

In this paper, we apply the learning of the mobile robot insect augmented reality Digilog Book. In the era of electronic, book written in paper space just have moved to virtual reality space. The virtual reality, constraints spatial and physical, in the real world, it is a technique that enables to experience indirectly situation not experienced directly as user immersive experience type interface. Applied to the learning robot Digilog Book that allows the fusion of paper analog and digital content, using the augmented reality technology, to experience various interactions. Apply critical elements moving, three-dimensional images and animation to enrich the learning, for easier block assembly, designed to grasp more easily rank order between the blocks. Anywhere at any time, is capable of learning of the robot in Digilog Book to be executed by the mobile phone in particular.

• Journal of the Korea Computer Graphics Society
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• v.24 no.4
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• pp.39-54
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• 2018

Recently, augmented reality(AR) based building information applications using a smart phone provide information in the static form irrespective of the distance between a user and a target building. If many target buildings are located close to each other, discrimination of information is reduced due to overlapping information objects. Furthermore, it is difficult to intuitively grasp the current position of the user in the previous AR-based applications. In this paper, to solve these limitations, we have designed and implemented a novel building information system in which the location and size of information objects are adaptively displayed according to locations of a user and target buildings, and which allows users to intuitively understand their location by providing a 3D map that displays the user's location and all target buildings within a given distance in real-time. The AR-based building information application proposed in this paper focuses on the building guide in Deoksu Palace in Jung-gu, Seoul.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.5
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• pp.1199-1206
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• 2015

This paper introduces an algorithm for computing similarity between two poses in the motion capture data with different scale of skeleton, different number of joints and different joint names. The proposed algorithm first performs the topological analysis on the skeleton hierarchy for classifying the joints into more meaningful groups. The global joints positions of each joint group then are aggregated into a point cloud. The number of joints and their positions are automatically adjusted in this process. Once we have two point clouds, the algorithm finds an optimal 2D transform matrix that transforms one point cloud to the other as closely as possible. Then, the similarity can be obtained by summing up all distance values between two points clouds after applying the 2D transform matrix. After some experiment, we found that the proposed algorithm is able to compute the similarity between two poses regardless of their scale, joint name and the number of joints.

• Journal of Korea Multimedia Society
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• v.13 no.12
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• pp.1832-1842
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• 2010

This paper introduces a new automatic processing system: "Contents Factory" for the mass production of contents. Through the contents factory, we provide an authoring environment to improve the usability and the efficiency in producing contents. The contents factory integrates recycling techniques for contents resources, contents development engines, authoring tools, and interfaces into a total processing system. Since it is multi-platform based including mobile devices as well as PCs, one can easily produce complete PC and mobile contents from raw resources. We produced an example, "Sejong square" via the contents factory in order to demonstrate its effectiveness and usability.

• 한국공간정보시스템학회:학술대회논문집
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• 2004.12a
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• pp.169-181
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• 2004

SK Telecom has already constructed GIMS system as the base common framework of LBS/GIS service system based on OGC(OpenGIS Consortium)'s international standard for the first mobile vector map service in 2002, But as service content appears more complex, renovation has been needed to satisfy multi-purpose, multi-function and maximum efficiency as requirements have been increased. This research is for preparation ion of GML3-based platform to upgrade service from GML2 based GIMS system. And with this, it will be possible for variety of application services to provide location and geographic data easily and freely. In GML 3.0, it has been selected animation, event handling, resource for style mapping, topology specification for 3D and telematics services for mobile LBS multimedia service. And the schema and transfer protocol has been developed and organized to optimize data transfer to MS(Mobile Stat ion) Upgrade to GML 3.0-based GIMS system has provided innovative framework in the view of not only construction but also service which has been implemented and applied to previous research and system. Also GIMS channel interface has been implemented to simplify access to GIMS system, and service component of GIMS internals, WFS and WMS, has gotten enhanded and expanded function.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.109-122
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• 2014

People are nowadays creating a tremendous amount of data on Social Network Service (SNS). In particular, the incorporation of SNS into mobile devices has resulted in massive amounts of data generation, thereby greatly influencing society. This is an unmatched phenomenon in history, and now we live in the Age of Big Data. SNS Data is defined as a condition of Big Data where the amount of data (volume), data input and output speeds (velocity), and the variety of data types (variety) are satisfied. If someone intends to discover the trend of an issue in SNS Big Data, this information can be used as a new important source for the creation of new values because this information covers the whole of society. In this study, a Twitter Issue Tracking System (TITS) is designed and established to meet the needs of analyzing SNS Big Data. TITS extracts issues from Twitter texts and visualizes them on the web. The proposed system provides the following four functions: (1) Provide the topic keyword set that corresponds to daily ranking; (2) Visualize the daily time series graph of a topic for the duration of a month; (3) Provide the importance of a topic through a treemap based on the score system and frequency; (4) Visualize the daily time-series graph of keywords by searching the keyword; The present study analyzes the Big Data generated by SNS in real time. SNS Big Data analysis requires various natural language processing techniques, including the removal of stop words, and noun extraction for processing various unrefined forms of unstructured data. In addition, such analysis requires the latest big data technology to process rapidly a large amount of real-time data, such as the Hadoop distributed system or NoSQL, which is an alternative to relational database. We built TITS based on Hadoop to optimize the processing of big data because Hadoop is designed to scale up from single node computing to thousands of machines. Furthermore, we use MongoDB, which is classified as a NoSQL database. In addition, MongoDB is an open source platform, document-oriented database that provides high performance, high availability, and automatic scaling. Unlike existing relational database, there are no schema or tables with MongoDB, and its most important goal is that of data accessibility and data processing performance. In the Age of Big Data, the visualization of Big Data is more attractive to the Big Data community because it helps analysts to examine such data easily and clearly. Therefore, TITS uses the d3.js library as a visualization tool. This library is designed for the purpose of creating Data Driven Documents that bind document object model (DOM) and any data; the interaction between data is easy and useful for managing real-time data stream with smooth animation. In addition, TITS uses a bootstrap made of pre-configured plug-in style sheets and JavaScript libraries to build a web system. The TITS Graphical User Interface (GUI) is designed using these libraries, and it is capable of detecting issues on Twitter in an easy and intuitive manner. The proposed work demonstrates the superiority of our issue detection techniques by matching detected issues with corresponding online news articles. The contributions of the present study are threefold. First, we suggest an alternative approach to real-time big data analysis, which has become an extremely important issue. Second, we apply a topic modeling technique that is used in various research areas, including Library and Information Science (LIS). Based on this, we can confirm the utility of storytelling and time series analysis. Third, we develop a web-based system, and make the system available for the real-time discovery of topics. The present study conducted experiments with nearly 150 million tweets in Korea during March 2013.