• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.111-116
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• 2002

The types of service using location Information are being various and extending it's domain as wireless internet technology is developing and it's application part is widespread, so it is prospected that LBS (Location-Based Services) will be killer application in wireless internet services. This location information is basic and high value-added information, and this information services make prior GIS (Geography Information System) to be useful to anybody. The acquisition of this location information from moving object is very important part for these LBS. After this, when LBS is familiar to everybody, we can predict that LBS system load is so heavy for the acquisition of so many subscribers and vehicles. Moving object database (MODB) system manages objects like subscribes and vehicles that are moving and have telecommunication terminal checked one's location. MODB is consists of 4 part, moving object location acquisition part, moving object location storage part, moving object query processing part, and moving object application p art. In this MODB system, acquisition of moving object location part must provide guarantee location information as well as reduce telecommunication overhead. In this paper, we study of problems in acquisition a huge number o f moving objects location and design some acquisition strategies to reduce telecommunication overhead. And after implementation these strategies, we estimate performance of this system and quality of information.

• Journal of Korea Spatial Information System Society
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• v.1 no.2 s.2
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• pp.127-135
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• 1999

Currently, many geographic information systems deal with only vector data. Therefore, handling raster data for various types of information is greatly needed. In this paper, we design and implement a raster processor which handles spatial information in a spatial object management system called Object Management system for Geospatial Application (OMEGA). We define the data structure of the raster information to be stored in the spatial object management system and implement it to a class library in order for use in making an application program. Furthermore, a query operation and related module is implemented to extract raster information. They are then imbedded in the query executer to process a query of the raster information. Simulation results are given.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.3
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• pp.422-428
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• 2008

In this paper, we propose the robust object detection algorithm with spatial gradient information. To do this, first, we eliminate error values that appear due to complex environment and various illumination change by using prior methods based on hue and intensity from the input video and background. Visible shadows are eliminated from the foreground by using an RGB color model and a qualified RGB color model. And unnecessary values are eliminated by using the HSI color model. The background is removed completely from the foreground leaving a silhouette to be restored using spatial gradient and HSI color model. Finally, we validate the applicability of the proposed method using various indoor and outdoor conditions in a complex environments.

• Journal of KIISE:Software and Applications
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• v.26 no.10
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• pp.1178-1178
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• 1999

A spatial join has the property that its execution time exponentially increases in proportion to the number of spatial objects. Recently, there have been many attempts for improving the performance of the spatial join by using parallel processing schemes, In the case of executing parallel spatial join using the parallel machine with shared disk architecture, the disk bottleneck of parallel processing of spatial join worsens in comparison with sequential spatial join. This paper presents the algorithms of task creation and assignment to reduce the disk bottleneck caused by accessing the shared disk at the same time, and to minimize message passing between processors, This paper proposes object caching which is a higher level of abstraction than page caching, and uses it to do creation and assignment of tasks according to temporal and spatial localities for minimizing disk access time. The object caching shows the performance improvement of 50%. The task creation and assignment using localities gives the gain of 30% and 20%. Overall performance evaluation of the proposed algorithms shows 7.2 times speed up than those of sequential execution of spatial joins.

• Journal of Korea Spatial Information System Society
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• v.9 no.3
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• pp.1-16
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• 2007

A spatial data warehouse is a system to support decision making using a spatial data cube. A spatial data cube is composed of a dimension table and a fact table. For decision support using this spatial data cube, the concept hierarchy of spatial dimension and the summarized information of spatial fact should be provided. In the previous researches, however, spatial summarized information is deficient. In this paper, the spatial aggregation for spatial summarized information in a spatial data warehouse is proposed. The proposed spatial aggregation is separated of both the numerical aggregation and the object aggregation. The numerical aggregation is the operation to return a numerical data as a result of spatial analysis and the object aggregation returns the result represented to object. We provide the extended struct of spatial data for spatial aggregation and so our proposed method is efficient.

• ETRI Journal
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• v.40 no.2
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• pp.246-256
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• 2018

A spatial augmented reality (SAR) system enables a virtual image to be projected onto the surface of a real-world object and the user to intuitively control the image using a tangible interface. However, occlusions frequently occur, such as a sudden change in the lighting environment or the generation of obstacles. We propose a robust object tracker based on a multithreaded system, which can track an object robustly through occlusions. Our multithreaded tracker is divided into two threads: the detection thread detects distinctive features in a frame-to-frame manner, and the tracking thread tracks features periodically using an optical-flow-based tracking method. Consequently, although the speed of the detection thread is considerably slow, we achieve real-time performance owing to the multithreaded configuration. Moreover, the proposed outlier filtering automatically updates a random sample consensus distance threshold for eliminating outliers according to environmental changes. Experimental results show that our approach tracks an object robustly in real-time in an SAR environment where there are frequent occlusions occurring from augmented projection images.

• The KIPS Transactions:PartD
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• v.13D no.6 s.109
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• pp.789-796
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• 2006

Context-aware is the core in ubiquitous environment of sensor network to support intelligent and contextual adaptation service. The new context information model is demanded to support context-aware applications. The model should not depend on a specified application and be shareable between applications in the same environment. Also, it should support various context representation and complex context-aware. In this paper, we define the context information according to context-aware process. Also we design the knowledge of domain as well as applications using ontologies and rules. The domain spatial ontology and application knowledge are represented using the spatial object model and the rules of expanded ontologies, respectively. The expression of abundant spatial ontology represents the context information about distance between objects and adjacent object as well as the location of the object. The proposed context information model which is able to exhibit various spatial context and recognizes complex spatial context through the existing GIS. This model shows that it can adapt to a large scale outdoor context-aware applications such as air pollution and prevention of disasters as well as various context-aware applications.

• Journal of KIISE:Software and Applications
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• v.26 no.10
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• pp.1167-1167
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• 1999

Although spatial databases support an efficient spatial management on objects in the real world, they have a characteristic that process only spatial information valid at current time, So in case of change in the spatial domain, it is very hard to support an efficient historical management for time-varying spatial information because they delete an old value and then replace with new value that is valid at current time. To solve these problems, there are rapidly increasing of interest for spatiotemporal databases, which serve historical functions for spatial information as well as spatial management functions for an object. However most of them presented in an abstract time-varying spatial phenomenon, but have not presented a concrete policy in spatiotemporal databases. In this paper, we propose a spatiotemporal data model that supports bitemporal time concepts in three dimensional architecture. In the proposed model, not only data types and their operation for object of spatiotemporal databases have been classified, but also mathematical expressions using formal semantics for them have been given. Then, the data structures and their operations based on relational database model as well as object-oriented database model are presented.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.885-890
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• 2002

As Geographic Information Systems represents three-dimensional topological Information, the systems provide accurate and delicate services for user. In order to execute three-dimensional topological operations, a dimensional transformation and heterogeneous spatial models should be used. However, the existing systems that use the dimensional transformation and the heterogeneous models, are not only difficult to operate the spatial operators, but also happened to support non- interoperability. Therefore, in order to support the spatial operation as well as interoperability between dimensions, we propose three-dimensional spatial operators for the proposed models. We defined the three-dimensional spatial operators prior to designing the proposed model. We also implemented the operators of proposed model and evaluated the implemented model on the component environment. Finally, the proposed model is able to not only support interoperability among systems but also execute spatial queries efficiently on three-dimensional spatial objects.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.11
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• pp.2737-2753
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• 2013

In this study, we propose a novel salient object detection strategy based on regional contrast and relative spatial compactness. Our algorithm consists of four basic steps. First, we learn color names offline using the probabilistic latent semantic analysis (PLSA) model to find the mapping between basic color names and pixel values. The color names can be used for image segmentation and region description. Second, image pixels are assigned to special color names according to their values, forming different color clusters. The saliency measure for every cluster is evaluated by its spatial compactness relative to other clusters rather than by the intra variance of the cluster alone. Third, every cluster is divided into local regions that are described with color name descriptors. The regional contrast is evaluated by computing the color distance between different regions in the entire image. Last, the final saliency map is constructed by incorporating the color cluster's spatial compactness measure and the corresponding regional contrast. Experiments show that our algorithm outperforms several existing salient object detection methods with higher precision and better recall rates when evaluated using public datasets.