• Proceedings of the KSRS Conference
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• v.2
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• pp.725-727
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• 2006

The development of GIS and Location-Based Services requires a high-level database that will be able to allow real-time access to moving objects for spatial and temporal operations. MODB.MM is able to meet these requirements quite adequately, providing operations with the abilities of acquiring, storing, and querying large-scale moving objects. It enables a dynamic and diverse query mechanism, including searches by region, trajectory, and temporal location of a large number of moving objects that may change their locations with time variation. Furthermore, MODB.MM is designed to allow for performance upon main memory and the system supports the migration on out-of-date data from main memory to disk. We define the particular query for truncation of moving objects data and design two migration methods so as to operate the main memory moving objects database system and file-based location storage system with.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.287-290
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• 2004

In the moving object database system, spatiotemporal join is very import operation when we process join moving objects. Processing time of spatio-temporal join operation increases by geometric progression with numbers of moving objects. Therefore efficient methods of spatio-temporal join is essential to moving object database system. In this paper, we propose spatio-temporal join algorithm with TB-Tree that preserves trajectories of moving objects, and show result of test. We first present basic algorithm, and propose cpu-time tunning algorithm and IO-time tunning algorithm. We show result of test with data set created by moving object generator tool.

• International Journal of Control, Automation, and Systems
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• v.1 no.1
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• pp.119-126
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• 2003

The problem of tracking moving objects in a video stream is discussed in this pa-per. We discussed the popular technique of optical flow for moving object detection. Optical flow finds the velocity vectors at each pixel in the entire video scene. However, optical flow based methods require complex computations and are sensitive to noise. In this paper, we proposed a new method based on the Hough transform and on voting accumulation for improving the accuracy and reducing the computation time. Further, we applied the Boo-lean based edge detector for edge detection. Edge detection and segmentation are used to extract the moving objects in the image sequences and reduce the computation time of the CHT. The Boolean based edge detector provides accurate and very thin edges. The difference of the two edge maps with thin edges gives better localization of moving objects. The simulation results show that the proposed method improves the accuracy of finding the optical flow vectors and more accurately extracts moving objects' information. The process of edge detection and segmentation accurately find the location and areas of the real moving objects, and hence extracting moving information is very easy and accurate. The Combinatorial Hough Transform and voting accumulation based optical flow measures optical flow vectors accurately. The direction of moving objects is also accurately measured.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.14 no.3
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• pp.249-262
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• 1989

We present a method of boundary extraction of moving objects. We propose four methods for detecting moving edge pixels which can be located on the boundaries of moving objects. We select the best one after we test the above four methods to real image sequences. The portion of the boundaries of moving objects which is marked as moving edge pixels is searched along the moving edge pixels with simple heuristics. And the end points of the resultant line segments are utilized as the start points of the secon stage heuristic search. This second stage search is performed for the boundaries of moving objects which is not marked as moving edge pixels due to various reasons. We test our algorithm for two real sequences and we find that this simple algorithm has good performance.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.455-457
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• 2003

Diverse researches are working moving objects. The most important activities in a moving object database system are query and analysis of spatio -temporal data providing decision-making and problem solving support. Traditional spatial database query language and tools are inappropriate of the real world entities. This paper presents a spatio-temporal query and analysis tool with visual environment. It provides effective, interactive and user-friendly as well as statistic analysis. The moving objects database system stores plentiful moving objects data and performs spatio-temporal and nonspatio-temporal queries.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.7
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• pp.1815-1830
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• 2012

Existing R-tree that is based on a variety of outdoor-based techniques to manage moving objects have been investigated. Due to the different characteristics of the indoor and outdoor, it is difficult to management of moving object using existed methods in indoor setting. We propose a new index structure called ACII(adaptive Cell-based index for Indoor moving objects) for Indoor moving objects. ACII is Cell-based access structure adopting an overlapping technique. The ACII refines cells adaptively to handle indoor regional data, which may change its locations over time. The ACII consumed at most 30% of the space required by R-tree based methods, and achieved higher query performance compared with r-tree based methods.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.8
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• pp.41-53
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• 1993

The tasks which detect and track moving objects, by analyzing dynamic images taken at a constant time interval, are essential in various applications. This paper suggests how to utilize domain-specific knowledge and motional knowledge for detecting and tracking moving objects. That is, The trajectory information of a moving object is to be used for generating hypotheses on expected motion and expected position of moving objects, and the domain-specific knowledge is to be used for verifying the generated hypotheses.

• Journal of Korea Spatial Information System Society
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• v.7 no.1 s.13
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• pp.63-76
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• 2005

Recently, the wireless positioning techniques and mobile computing techniques were developed with rapidly to use location data of moving objects. Also, the demand for LBS(Location Based Services) which uses location data of moving objects is increasing rapidly. In order to support various LBS, a system that can store and retrieve location data of moving objects efficiently is required necessarily. The more the number of moving objects is numerous and the more periodical sampling of locations is frequent, the more location data of moving objects become very large. Hence the system should be able to efficiently manage mass location data, support various spatio-temporal queries for LBS, and solve the uncertainty problem of moving objects. Therefore, in this paper, we presented a hash technique, a clustering technique and a trajectory search technique to manage location data of moving objects efficiently And, we have developed a Mass Moving Object Location Data Management System, which is a disk-based system, that can store and retrieve location data of mass moving objects efficiently and support the query for spatio-temporal data and the past location data with uncertainty. By analying the performance of the Mass Moving Object Locations Management system and the SQL-Server, we can find that the performance of our system for storing and retrieving location data of moving objects was about 5% and 300% better than the SQL-Server, repectively.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.663-666
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• 2005

The Geography Markup Language (GML) is an XML encoding for the transport and storage of geographic information, including both the geometry and properties of geographic features. This paper uses the GML to provide extendibility and interoperability of spatial data in moving objects management system. Since the purpose of the system is to provide locations of the moving objects in the web and mobile environments, we used the GML both for presenting map data and trajectories of the moving objects. The proposed system is composed of Location Data Interface, Moving Objects Engine, and Web/Mobile Presentation Interface. We utilized the concept of Web Map Server, that is web mapping technology of OGC (Open Geospatial Consortium), to integrate map data and the location information of the moving objects. In the process of the integration, we used the standard data model and interfaces while defining new application schema. Since our suggested system uses open spatial data encoding and interfaces, both extendibility and interoperability are guaranteed.

• Proceedings of the IEEK Conference
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• 2001.06d
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• pp.219-222
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• 2001

Moving objects in video data are main elements for video analysis and retrieval. In this paper, we propose a new algorithm for tracking and segmenting moving objects in color image sequences that include complex camera motion such as zoom, pan and rotating. The Proposed algorithm is based on the Mean-shift color segmentation and stochastic region matching method. For segmenting moving objects, each sequence is divided into a set of similar color regions using Mean-shift color segmentation algorithm. Each segmented region is matched to the corresponding region in the subsequent frame. The motion vector of each matched region is then estimated and these motion vectors are summed to estimate global motion. Once motion vectors are estimated for all frame of video sequences, independently moving regions can be segmented by comparing their trajectories with that of global motion. Finally, segmented regions are merged into the independently moving object by comparing the similarities of trajectories, positions and emerging period. The experimental results show that the proposed algorithm is capable of segmenting independently moving objects in the video sequences including complex camera motion.