• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.567-571
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• 2009

Sports game broadcasting system uses multiple video cameras in order to offer exciting and dynamic scenes for the TV audiences. Since, however, the traditional broadcasting system edits the multiple views into a static video stream, it is difficult to provide the intelligent broadcasting service that summarizes or retrieves specific scenes or events based on the user preference. In this paper, we propose the summarization and retrieval system for the soccer videos based on multiple cameras. It extracts the highlights such as shot on goal, crossing, foul, and set piece using dynamic Bayesian network based on soccer players' primitive behaviors annotated on videos, and selects a proper view for each highlight according to its type. The proposed system, therefore, offers users the highlight summarization or preferred view selection, and can provide personalized broadcasting services by considering the user's preference.

• Journal of the Korea Computer Graphics Society
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• v.8 no.2
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• pp.15-22
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• 2002

Image segmentation methods partition an image into meaningful regions. For image composition and analysis, it is desirable for the partitioned regions to represent meaningful objects in terms of human perception and manipulation. Despite the recent progress in image understanding, however, most of the segmentation methods mainly employ low-level image features and it is still highly challenging to automatically segment an image based on high-level meaning suitable for human interpretation. The concept of HCI (Human Computer Interaction) can be applied to operator-assisted image segmentation in a manner that a human operator provides guidance to automatic image processing by interactively supplying critical information about object boundaries. Intelligent Scissors and Snakes have demonstrated the effectiveness of human-assisted segmentation [2] [1]. This paper presents a method for interactive image segmentation for more efficient and effective detection and tracking of object boundaries. The presented method is partly based on the concept of Intelligent Scissors, but employs the well-established Canny edge detector for stable edge detection. It also uses "sewing method" for including weak edges in object boundaries, and 5-direction search to promote more efficient and stable linking of neighboring edges than the previous methods.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.11
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• pp.153-161
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• 2013

Recently, there has been a tremendous increase in the availability of educational materials for foreign language learning. As part of this trend, there has been an increase in the amount of electronically mediated materials available. However, conventional educational contents developed using computer technology has provided typically one-way information, which is not the most helpful thing for users. Providing the user's convenience requires additional off-line analysis for diagnosing an individual user's learning. To improve the user's comprehension of texts written in a foreign language, we propose an intelligent learning tool based on the analysis of the user's eyeball movements, which is able to diagnose and improve foreign language reading ability by providing necessary supplementary aid just when it is needed. To determine the user's learning state, we correlate their eye movements with findings from research in cognitive psychology and neurophysiology. Based on this, the learning tool can distinguish whether users know or do not know words when they are reading foreign language sentences. If the learning tool judges a word to be unknown, it immediately provides the student with the meaning of the word by extracting it from an on-line dictionary. The proposed model provides a tool which empowers independent learning and makes access to the meanings of unknown words automatic. In this way, it can enhance a user's reading achievement as well as satisfaction with text comprehension in a foreign language.

• The Journal of the Korea Contents Association
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• v.17 no.11
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• pp.389-397
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• 2017

Recently semantic web document is produced and added in repository in a cloud computing environment and requires an intelligent semantic agent for analytical classification of documents and information retrieval. The traditional methods of information retrieval uses keyword for query and delivers a document list returned by the search. Users carry a heavy workload for examination of contents because a former method of the information retrieval don't provide a lot of semantic similarity information. To solve these problems, we suggest a key word frequency and concept matching based semantic clustering model using hadoop and NoSQL to improve classification accuracy of the similarity. Implementation of our suggested technique in a cloud computing environment offers the ability to classify and discover similar document with improved accuracy of the classification. This suggested model is expected to be use in the semantic web retrieval system construction that can make it more flexible in retrieving proper document.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.6
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• pp.85-91
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• 2020

Recently, video-taping equipment such as CCTV have been seeing more use for crime prevention and general safety concerns. Since these video-taping equipment operates all throughout the day, the need for security personnel is lessened, and naturally costs incurred from managing such manpower should also decrease. However, technology currently used predominantly lacks self-sufficiency when given the task of searching for a specific object in the recorded video such as a person, and has to be done manually; current security-based video equipment is insufficient in an environment where real-time information retrieval is required. In this paper, we propose a technology that uses the latest deep-learning technology and OpenCV library to quickly search for a specific person in a video; the search is based on the clothing information that is inputted by the user and transmits the result in real time. We implemented our system to automatically recognize specific human objects in real time by using the YOLO library, whilst deep learning technology is used to classify human clothes into top/bottom clothes. Colors are also detected through the OpenCV library which are then all combined to identify the requested object. The system presented in this paper not only accurately and quickly recognizes a person object with a specific clothing, but also has a potential extensibility that can be used for other types of object recognition in a video surveillance system for various purposes.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.4 no.2
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• pp.443-451
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• 2000

Until now, there have been various kinds of science information databsae which databased the science technology information, but they do not satisfy the aspiration of the users. Therefore, in the position of the users, it suggests the technology information space as a now paradigm, which supplement the function of science information DB. ICPIS which inputs described papers with keywords, offers the itemized summary of these contents, the visual indication and comparison of similar thesis, and it also supplises the abundant summary information, survey information, more than ten volumes of info communication thesis with starting the casual relation extraction for the users, playing a significant role in ICPIS is called KP, and it is package of domain knowledge that unifies the extraction and structure narration of the technology information. ICPIS extracts the technology information among the thesis that are deserved by the natural language treatment in the itemized KP keywords described, and form the prescribed summary structure in KP.

• The KIPS Transactions:PartD
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• v.13D no.7 s.110
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• pp.985-996
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• 2006

As the internet technologies develop, the geographic information system environment is changing to the web-based service. Since geospatial information of the existing Web-GIS services were developed independently, there is no interoperability to support diverse map formats. In spite of the same geospatial information object it can be used for various proposes that is duplicated in GIS separately. It needs intelligent strategies for optimal replica selection, which is identification of replication geospatial information objects. And for management of replication objects, OMG, GLOBE and GRID computing suggested related frameworks. But these researches are not thorough going enough in case of geospatial information object. This paper presents a model of location service, which is supported for optimal selection among replication and management of replication objects. It is consist of tree main services. The first is binding service which can save names and properties of object defined by users according to service offers and enable clients to search them on the service of offers. The second is location service which can manage location information with contact records. And obtains performance information by the Load Sharing Facility on system independently with contact address. The third is intelligent selection service which can obtain basic/performance information from the binding service/location service and provide both faster access and better performance characteristics by rules as intelligent model based on rough sets. For the validity of location service model, this research presents the processes of location service execution with Graphic User Interface.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.4
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• pp.812-820
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• 2012

In this paper, multiple pedestrians tracking system using Histogram of Oriented Gradient and occlusion detection is proposed. The proposed system is applicable to Intelligent Surveillance System. First, we detect pedestrian in a image sequence using pedestrian's feature. To get pedestrian's feature, we make block-histogram using gradient's direction histogram based on HOG(Histogram of Oriented Gradient), after that a pedestrian region is classified by using Linear-SVM(Support Vector Machine) training. Next, moving objects are tracked by using position information of the classified pedestrians. And we create motion trajectory descriptor which is used for content based event retrieval. The experimental results show that the proposed method is more fast, accurate and effective than conventional methods.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.10
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• pp.962-974
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• 2010

Recently, the convergence of information technology with bio-technology, nano-technology or other technologies has been creating a new paradigm. In a field of transportation, the intelligent transport systems which is a convergence of intelligent technologies and transportation systems have been studied. The Variable Speed Limit(VSL), is one of ITS technologies, is thought to improve safety and efficiency of transportation while controlling speed limit based on road conditions. Legacy studies have considered only one station for VSL algorithm. However, it is not appropriate for an urban freeway installed with many stations. In this paper, new algorithm is proposed to not only enhance effectiveness of VSL based on cooperation of stations but also reflect road conditions within 30 seconds. The proposed algorithm consists of 4 steps: the first is a "searching bottleneck station" step, the second is a "calculating a size of congestion" step, the third is a "calculating the number of controlled stations" step, the final is a "calculating VSL" step. This algorithm guarantees improved safety and minimum additional travel time. The travel time should be considered because drivers would against the VSL algorithm when the proposed algorithm occurs additional travel time. In our experiments, microscopic traffic simulator VISSIM is selected to perform a modeling work. The results show that proposed algorithm provides the improved safety and minimum increase of travel time.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.67-88
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• 2018

Until recently, as we recognize the significance of sustainable growth and competitiveness of small-and-medium sized enterprises (SMEs), governmental support for tangible resources such as R&D, manpower, funds, etc. has been mainly provided. However, it is also true that the inefficiency of support systems such as underestimated or redundant support has been raised because there exist conflicting policies in terms of appropriateness, effectiveness and efficiency of business support. From the perspective of the government or a company, we believe that due to limited resources of SMEs technology development and capacity enhancement through collaboration with external sources is the basis for creating competitive advantage for companies, and also emphasize value creation activities for it. This is why value chain network analysis is necessary in order to analyze inter-company deal relationships from a series of value chains and visualize results through establishing knowledge ecosystems at the corporate level. There exist Technology Opportunity Discovery (TOD) system that provides information on relevant products or technology status of companies with patents through retrievals over patent, product, or company name, CRETOP and KISLINE which both allow to view company (financial) information and credit information, but there exists no online system that provides a list of similar (competitive) companies based on the analysis of value chain network or information on potential clients or demanders that can have business deals in future. Therefore, we focus on the "Value Chain Network System (VCNS)", a support partner for planning the corporate business strategy developed and managed by KISTI, and investigate the types of embedded network-based analysis modules, databases (D/Bs) to support them, and how to utilize the system efficiently. Further we explore the function of network visualization in intelligent value chain analysis system which becomes the core information to understand industrial structure ystem and to develop a company's new product development. In order for a company to have the competitive superiority over other companies, it is necessary to identify who are the competitors with patents or products currently being produced, and searching for similar companies or competitors by each type of industry is the key to securing competitiveness in the commercialization of the target company. In addition, transaction information, which becomes business activity between companies, plays an important role in providing information regarding potential customers when both parties enter similar fields together. Identifying a competitor at the enterprise or industry level by using a network map based on such inter-company sales information can be implemented as a core module of value chain analysis. The Value Chain Network System (VCNS) combines the concepts of value chain and industrial structure analysis with corporate information simply collected to date, so that it can grasp not only the market competition situation of individual companies but also the value chain relationship of a specific industry. Especially, it can be useful as an information analysis tool at the corporate level such as identification of industry structure, identification of competitor trends, analysis of competitors, locating suppliers (sellers) and demanders (buyers), industry trends by item, finding promising items, finding new entrants, finding core companies and items by value chain, and recognizing the patents with corresponding companies, etc. In addition, based on the objectivity and reliability of the analysis results from transaction deals information and financial data, it is expected that value chain network system will be utilized for various purposes such as information support for business evaluation, R&D decision support and mid-term or short-term demand forecasting, in particular to more than 15,000 member companies in Korea, employees in R&D service sectors government-funded research institutes and public organizations. In order to strengthen business competitiveness of companies, technology, patent and market information have been provided so far mainly by government agencies and private research-and-development service companies. This service has been presented in frames of patent analysis (mainly for rating, quantitative analysis) or market analysis (for market prediction and demand forecasting based on market reports). However, there was a limitation to solving the lack of information, which is one of the difficulties that firms in Korea often face in the stage of commercialization. In particular, it is much more difficult to obtain information about competitors and potential candidates. In this study, the real-time value chain analysis and visualization service module based on the proposed network map and the data in hands is compared with the expected market share, estimated sales volume, contact information (which implies potential suppliers for raw material / parts, and potential demanders for complete products / modules). In future research, we intend to carry out the in-depth research for further investigating the indices of competitive factors through participation of research subjects and newly developing competitive indices for competitors or substitute items, and to additively promoting with data mining techniques and algorithms for improving the performance of VCNS.