• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.407-409
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• 2015

In this paper, a hardware implementation of MOD(Moving Object Detection) algorithm is described, which is based GMM(Gaussian Mixture Model) and background subtraction. The EGML(Effective Gaussian Mixture Learning) is used to model and update background. Some approximations of EGML calculations are applied to reduce hardware complexity, and pipelining technique is used to improve operating speed. Gaussian parameters are adjustable according to various environment conditions to achieve better MOD performance. MOD processor is verified by using FPGA-in-the-loop verification, and it can operate with 109 MHz clock frequency on XC5VSX95T FPGA device.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.371-373
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• 2015

This paper describes an analysis of hardware design conditions of moving object detection algorithm which is based on effective Gaussian mixture learning (EGML). The simulation model of EGML algorithm is implemented using OpenCV, and it is analyzed that the effects of parameter values on background learning time and moving object detection sensitivity for various images. In addition, optimal design conditions for hardware implementation of EGML-based MOD algorithm are extracted from fixed-point simulations for various bit-width parameters.

• 한국공간정보시스템학회:학술대회논문집
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• 2004.12a
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• pp.105-112
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• 2004

최근 이동 객체의 위치정보를 활용한 위치 찾기 서비스, 교통 정보 서비스, 긴급 구조 서비스, 모바일 광고 서비스와 같은 위치 기반 서비스가 부각되고 있다. 이와 같은 다양한 위치 기반 서비스를 제공하기 위해서는 대용량의 이동 객체의 위치정보를 신속하게 저장, 검색, 갱신할 수 있는 저장시스템이 필수적으로 요구된다. 그러나, 이동 객체 위치정보 저장시스템으로 기존의 데이타베이스 시스템을 사용할 경우 불필요한 트랜잭션 연산으로 인하여 저장 및 검색 시 오버헤드가 발생하고, 위치 기반 서비스에 필요한 다양한 질의 및 요구사항을 지원하지 못한다는 문제점이 있다. 따라서, 본 논문에서는 대용량의 위치정보를 효과적으로 저장 및 검색할 수 있으며, 위치 기반 서비스에서 요구하는 궤적 질의 기능, 위치 트리거 기능, 위치 보정 기능, 이동 객체 아이디 기반 클러스터 기능 등을 지원하는 대용량 위치정보 저장시스템을 개발하였다. 또한, 대용량 위치정보 저장시스템의 성능 평가를 위해서 상용 데이타베이스 시스템인 SQL-Server와 비교 실험하여 성능의 우수함을 입증하였다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.360-363
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• 2015

In n-dimensional spatial data, Minimum Boundary Rectangle(MBR) was used to handle the moving object trajectories data. But, this method has inaccurate approximation. So, It makes many dead space and performs unnecessary operation when processing a query. In this paper, we offer new index structure using approximation. We developed algorithm that make index strucutre by using Douglas-Peucker Algorithm and had a comparison experiment.

• Convergence Security Journal
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• v.8 no.4
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• pp.97-104
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• 2008

Recently, the wireless positioning techniques and mobile computing techniques have rapidly developed to use location data of moving objects. 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, innovating the location data of moving object effectively, we propose Rend 3DR-tree method to decrease the dead space and complement the overlapping of nodes by utilizing 3DR-tree with the indexing structure to support indexing of current data and history data.

• Spatial Information Research
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• v.19 no.2
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• pp.57-64
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• 2011

This paper describes how to storing and querying trajectory information on PostgreSQL/PostGIS. Recently as technology of mobile devices is advancing, many researches for location-based services and moving object's trajectory have been studied. Trajectory is the set of information of the location by the time, and is one of the most im portant information for location-based services. Traditional spatial database systems do not support trajectory data types and functions. In this paper, we propose a trajectory data type and query functions for moving objects on PostgreSQL/PostGIS.

• Proceedings of the Korean Information Science Society Conference
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• 2005.07b
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• pp.49-51
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• 2005

시간의 흐름에 따라 그 위치가 빈번히 변화하는 이동 객체의 특성으로 인해 실시간으로 증가하는 이동객체의 연산 정보를 효과적으로 관리할 수 있는 효율적인 연산 기법이 요구된다. 따라서 본 논문에서는 이동 객체의 시공간 연산을 위해 기존에 제안되었던 HR 트리의 성능을 개선시킬 수 있는 확장된 HR-트리(Extended HR-Tree : EHR-Tree)를 제안한다. 기존의 HR 트리는 삽입, 삭제, 갱신과 같은 연산이 빈번한 경우에 단말 노드 및 비단말 노드를 새로 생성해야 함으로 인하여 성능이 떨어지고, 공간의 낭비가 있게 된다. 이 문제를 해결하기 위해 본 논문에서 제안하는 EHR-트리는 연산이 발생할 때마다 새로운 HR-트리를 생성하는 것이 아니라 시간 구간을 두어서 새로 발생한 연산이 같은 시간 구간에 있을 경우 그 단위시간에 생성된 HR-트리에 그대로 삽입, 삭제, 갱신과 같은 연산을 수행하게 된다. 따라서 기존 HR-트리에서 단말 노드 및 비단말 노드를 새로 생성해야함으로 발생되던 많은 저장 공간 요구를 감소시킴으로, 즉 전체 연산 크기를 작게 하여 디스크 I/O수를 감소시킴으로써, 시공간 질의의 처리 속도를 향상시켜 효율적인 질의가 가능하도록 한다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.2
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• pp.364-370
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• 2014

The management and analysis of spatio-temporal and multimedia data is a hot issue in database research because such data types are handled in manny applications. Querying databases of such a content is very important for these applications. This paper addresses algorithms that make index structure by using Douglas-Peucker Algorithm and process range query efficiently on moving objects trajectories. We compare and analyze our algorithms and MBR by experiments. Our algorithms make smaller size of index structure and process more efficiently.

• Journal of Platform Technology
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• v.11 no.1
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• pp.52-59
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• 2023

The importance of spatio-temporal trajectories for contact tracing has increased due to the recent COVID-19 pandemic. Spatio-temporal trajectories store time and spatial data of moving objects. In this paper, I propose query processing for spatio-temporal trajectories of moving objects. The spatio-temporal trajectory model of moving objects has point type spatial data for storing locations and timestamp type temporal data for time. A trajectory query is a query to search for pairs of users who have been in close contact by boarding the same bus. To process the trajectory query, I use the Geolife dataset provided by Microsoft. The proposed trajectory query processing method divides trajectory data by date and checks whether users' trajectories were nearby for each date to generate information about contacts as the result.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.5
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• pp.274-286
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• 2022

Multi-object tracking has been studied for a long time under computer vision and plays a critical role in applications such as autonomous driving and driving assistance. Multi-object tracking techniques generally consist of a detector that detects objects and a tracker that tracks the detected objects. Various publicly available datasets allow us to train a detector model without much effort. However, there are relatively few publicly available datasets for training a tracker model, and configuring own tracker datasets takes a long time compared to configuring detector datasets. Hence, the detector is often developed separately with a tracker module. However, the separated tracker should be adjusted whenever the former detector model is changed. This study proposes a system that can train a model that performs detection and tracking simultaneously using only the detector training datasets. In particular, a Siam network with augmentation is used to compose the detector and tracker. Experiments are conducted on public datasets to verify that the proposed algorithm can formulate a real-time multi-object tracker comparable to the state-of-the-art tracker models.