• Proceedings of the Korea Information Processing Society Conference
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• 2016.04a
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• pp.189-191
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• 2016

실시간 물리 기반 3D 시뮬레이션에서 연산속도는 매우 중요한 요소이다. 객체의 움직임이나 변형과 같은 현상들은 복잡한 연산을 통해서 계산되기 때문에 일반적으로 시뮬레이션의 정확도와 연산속도는 반비례 관계에 있다. 현재 출시되고 있는 대부분의 게임에서는 물체의 움직임을 정확하게 표현하기보다 연산량을 줄이기 위해 물체의 움직임이나 변형을 비슷하게 표현하는데 중점을 두고 있다. 본 논문에서는 이러한 문제를 해결하기 위하여 OpenGL 4.3의 Compute shader를 사용하여 다이내믹 시뮬레이션의 연산 작업을 GPU 병렬처리로 처리하였다. Compute shader에서 파티클의 움직임을 계산하고 Shader storage buffer object에 저장하고 파티클들의 작업량을 적절한 Workgroup의 크기로 나누어 할당하여 최적의 처리속도를 제공하도록 구현하였다. Compute shader에서 파티클의 움직임을 표현하기 위해서 수치해법 중의 하나인 Euler method를 사용하였으며 실험 결과 파티클의 수가 4,194,304개일 때 CPU 방법에 비해 약 182배 빠른 연산속도 결과를 보였다. 추후 Compute shader를 활용하여 연산량이 많은 분야에 적용 가능할 수 있을 것으로 기대한다.

• The KIPS Transactions:PartB
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• v.19B no.1
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• pp.27-30
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• 2012

One of the most fundamental functions required for an intelligent agent is to estimate its current position based upon uncertain sensor data. In this paper, we explain the implementation of a robot localization system using Particle filters, which are the most effective one of the probabilistic localization methods, and then present the result of experiments for evaluating the performance of our system. Through conducting experiments to compare the effect of the noise-free model with that of the noisy state transition model considering inherent errors of robot actions, we show that it can help improve the performance of the Particle filter localization to apply a state transition model closely approximating the uncertainty of real robot actions.

• Journal of KIISE:Software and Applications
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• v.33 no.12
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• pp.1022-1030
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• 2006

The location awareness is an important part of many ubiquitous computing systems, but a perfect location system does not exist yet in spite of many researches. Among various location tracking systems, we choose the RFID system due to its wide applications. However, the sensed RSSI signal is too sensitive to the direction of a RFID reader antenna, the orientation of a RFID tag, the human interference, and the propagation media situation. So, the existing location tracking method in spite of using the particle filter is not working well. To overcome this shortcoming, we suggest a robust location tracking method with a double layered structure, where the first layer coarsely estimates a tag's location in the block level using a regression technique or the SVM classifier and the second layer precisely computes the tag's location, velocity and direction using the particle filter technique. Its layered structure improves the location tracking performance by restricting the moving degree of hidden variables. Many extensive experiments show that the proposed location tracking method is so precise and robust to be a good choice for implementing the location estimation of a person or an object in the ubiquitous computing. We also validate the usefulness of the proposed location tracking method by implementing it for a real-time people monitoring system in a noisy and complicate workplace.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.11a
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• pp.1350-1353
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• 2013

자동차의 안전성 향상에 대한 연구는 오랜 기간 다양한 분야에서 진행되고 있다. 이 시스템은 단일 카메라를 이용하여 차선을 감지함으로써 차선 침범을 방지한다. 시스템은 파티클 필터를 이용해 도로 모델 파라미터를 조정하고 두 개의 detector가 도로 모델의 일치도를 계산한다. Detector는 차선의 모양과 색이라는 대표적인 특징을 이용한다. 파티클 필터를 전 프레임에서 사용한 모델 파라미터를 이용하여 신속한 처리를 한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.04a
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• pp.313-316
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• 2011

본 논문에서는 파티클 필터를 이용한 이동 로봇의 위치 추정 방법을 제안한다. 이동 로봇의 위치를 추정하기 위해알기 위해 이동 로봇에 설치되어 있는 초음파 센서를 이용하여 주변 환경과의 거리를 측정한다. 그리고 측정된 센서 값과 이동 동작의 불확실성을 고려하여, 위치 추정 오차를 줄이고자 가우스 확률분포와 파티클 필터 기법을 이용하여 이동 로봇의 위치를 추정한다. 본 논문에서는 구현된 시스템과 실험 결과를 소개한다.

• Journal of KIISE:Computing Practices and Letters
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• v.12 no.3
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• pp.208-217
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• 2006

This paper presents a cloth simulation technique that implements plastic deformation. Plasticity is the property that material does not restore completely to the original state once deformed, in contrast to elasticity. We model cloth using a particle model, and posit two kinds of connections between particles, i.e. the sequential connections between immediate neighbors, and the interlaced connections between every other neighbors. The sequential connections represent the compression and tension of cloth, and the interlaced connections the bending in cloth. The sequential connections are modeled by elastic springs, and the interlaced connections by elastic or plastic spring depending on the amount of the current deformation of the connections. Our model is obtained by adding plastic springs to the existing elastic particle model of cloth. Using the new model, we have been able to simulate bending wrinkles, permanently deformed wrinkles, and small wrinkles widely distributed over cloth. When constructing elastic and plastic spring models for sequential and interlaced connections, we took pain to prevent the stiffness matrix of the whole cloth system from being indefinite, in order to help achieve physical stability of the cloth motion equation and to improve the effectiveness of the numerical method.

• KIISE Transactions on Computing Practices
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• v.23 no.12
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• pp.660-669
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• 2017

In order to improve user accessibility and interactivity, system scalability, service speed, and a non-standard internet web environment, we developed a Web-based geovisualization system of oceanographic information using HTML5 and dynamic particles. In particular, oceanographic and meteorological data generated from a satellite remote sensing and radar measurement and a 3-dimensioanl numerical model, has the characteristics of a heterogeneous large-capacity multi-dimensional continuous spatial and temporal variability, based on geographic information. Considering those attributes, we applied dynamic particles represent the spatial and temporal variations of vector type oceanographic data. HTML5, WebGL, Canvas, D3, and Leaflet map libraries were also applied to handle various multimedia data, graphics, map services, and location-based service as well as to implement multidimensional spatial and statistical analyses such as a UV chart.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.47 no.4
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• pp.274-282
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• 2019

Vision-based navigation of unmaned aerial vehicle is a significant technology that can reinforce the vulnerability of the widely used GPS/INS integrated navigation system. However, the existing image matching algorithms are not suitable for matching the aerial image with the database. For the reason, this paper proposes particle filters using Gaussian mixture models to deal with matching between aerial image and database for vision-based navigation. The particle filters estimate the position of the aircraft by comparing the correspondences of aerial image and database under the assumption of Gaussian mixture model. Finally, Monte Carlo simulation is presented to demonstrate performance of the proposed method.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.2
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• pp.186-190
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• 2015

Intelligent vehicle plans motion and navigate itself based on the surrounding environment perception. Hence, the precise environment recognition is an essential part of self-driving vehicle. There exist many vulnerable road users (e.g. vehicle, pedestrians) on vehicular driving environment, the vehicle must percept all the dynamic obstacles accurately for safety. In this paper, we propose an multiple vehicle tracking algorithm using microwave radar. Our proposed system includes various special features. First, exceptional radar measurement model for vehicle, concentrated on the corner, is described by mixture density network (MDN), and applied to particle filter weighting. Also, to conquer the curse of dimensionality of particle filter and estimate the time-varying number of multi-target states, reversible jump markov chain monte carlo (RJMCMC) is used to sampling step of the proposed algorithm. The robustness of the proposed algorithm is demonstrated through several computer simulations.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.1
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• pp.106-111
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• 2011

Video-based detection and tracking of moving objects has been widely used in real-time monitoring systems and a videoconferencing. Also, because object motion tracking can be expanded to Human-computer interface and Human-robot interface, Moving object tracking technology is one of the important key technologies. If we can track a specified object in an environment of multiple moving objects, then there will be a variety of applications. In this paper, we introduce a specified object motion tracking using particle filter. The results of experiments show that particle filter can achieve good performance in single object motion tracking and a specified object motion tracking in an environment of multiple moving objects.