• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.174-177
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• 2008

In 3D gaming environment, it is important to simulate the physically plausible behaviors of gaming objects in real time. In particular, rigid body dynamics consists in the heart of most game physics. In this paper, we present a constraint-based rigid body simulation method using continuous collision detection as a collision detection method, and LCP formulation as a collision response method. The continuous collision detection method never misses any collisions and thus is able to accurately report the first time of collision as well as its associated colliding features. Moreover, since the number of colliding features is typically low, it also reduces the complexity in the LCP formulation.

• Asia-Pacific Journal of Business
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• v.9 no.2
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• pp.1-13
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• 2018

Physics simulation is an important part of many interactive 2D applications and collision detection and response is key component of this simulation. While methods for reducing the number of collision tests that need to be performed has been well researched, methods for performing the final checks with collision primitives have seen little recent development. This paper presents a new collision primitive, the n-arc, constructed from piecewise circular curves or biarcs. An algorithm for performing a collision check between these primitives is presented and compared to a convex polygon primitive. The n-arc is shown to exhibit similar, though slightly slower, performance to a polygon when no collision occurs, but is considerably faster when a collision does occur. The goodness of fit of the new primitive is also compared to a polygon. While the n-arc often gives a looser fit in terms of area, the continuous tangents of the n-arcs makes them a good choice for organic, soft or curved surfaces.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.07a
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• pp.569-572
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• 2022

본 논문에서는 공기 메쉬(Air meshes)를 이용하여 고체의 충돌을 효율적으로 처리할 수 있는 새로운 방법을 제시한다. 기존의 프리미티브 단위의 충돌 처리는 시뮬레이션의 안정성을 높이기 위해 시간 간격(Time-step), 3차 방정식과 같은 큰 계산 과정을 필요로 했으며, 장면 복잡도에 따라 DCD(Discrete collision detection)뿐만 아니라 CCD(Continuous collision detection)까지 고려해야 되는 상황이 빈번히 발생한다. 본 논문에서는 이전에 제안된 공기 메쉬 기법을 통해 충돌처리를 효율적으로 개선시킬 수 있는 방법에 대해서 제안한다. 원본 공기 메쉬 접근법은 시뮬레이션 메쉬가 아닌, 주변 공기를 메쉬화시키고 이들의 변형을 부피로 근사하여 충돌 여부 및 처리를 인지하고 예측했다. 공기 메쉬를 정제하는 과정에서 수치적인 수렴을 위해 정삼각형을 유지하려는 제약사항을 두었다. 하지만, 이러한 방법은 장면에 따라 노이즈한 결과를 나타내며, 헤어나 털 시뮬레이션과 같은 라인 형태인 시뮬레이션에서는 경계 문제가 더욱더 민감하게 나타났다. 본 논문에서는 공기 메쉬를 정제하는 과정에서 새로운 제약 조건을 추가하여 노이즈가 완화된 충돌처리 결과를 보여준다. 우리의 헤어뿐만 아니라 대부분의 장면에서 안정적인 결과를 보여준다.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.1243-1244
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• 2022

In recent years, the growing interest in off-site construction has led to factories scaling up their manufacturing and production processes in the construction sector. Consequently, continuous large-scale site monitoring in low-variability environments, such as prefabricated components production plants (precast concrete production), has gained increasing importance. Although many studies on computer vision-based site monitoring have been conducted, challenges for deploying this technology for large-scale field applications still remain. One of the issues is collecting and transmitting vast amounts of video data. Continuous site monitoring systems are based on real-time video data collection and analysis, which requires excessive computational resources and network traffic. In addition, it is difficult to integrate various object information with different sizes and scales into a single scene. Various sizes and types of objects (e.g., workers, heavy equipment, and materials) exist in a plant production environment, and these objects should be detected simultaneously for effective site monitoring. However, with the existing object detection algorithms, it is difficult to simultaneously detect objects with significant differences in size because collecting and training massive amounts of object image data with various scales is necessary. This study thus developed a large-scale site monitoring system using edge computing and a small-object detection system to solve these problems. Edge computing is a distributed information technology architecture wherein the image or video data is processed near the originating source, not on a centralized server or cloud. By inferring information from the AI computing module equipped with CCTVs and communicating only the processed information with the server, it is possible to reduce excessive network traffic. Small-object detection is an innovative method to detect different-sized objects by cropping the raw image and setting the appropriate number of rows and columns for image splitting based on the target object size. This enables the detection of small objects from cropped and magnified images. The detected small objects can then be expressed in the original image. In the inference process, this study used the YOLO-v5 algorithm, known for its fast processing speed and widely used for real-time object detection. This method could effectively detect large and even small objects that were difficult to detect with the existing object detection algorithms. When the large-scale site monitoring system was tested, it performed well in detecting small objects, such as workers in a large-scale view of construction sites, which were inaccurately detected by the existing algorithms. Our next goal is to incorporate various safety monitoring and risk analysis algorithms into this system, such as collision risk estimation, based on the time-to-collision concept, enabling the optimization of safety routes by accumulating workers' paths and inferring the risky areas based on workers' trajectory patterns. Through such developments, this continuous large-scale site monitoring system can guide a construction plant's safety management system more effectively.

• Journal of the Korea Computer Graphics Society
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• v.15 no.4
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• pp.1-11
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• 2009

In this paper, we present a prism-based mesh culling method to improve effectiveness of continuous collision detection which is a major bottleneck in a simulation using polygonal mesh models. A prism is defined based on two matching triangles between a sequence of times m a polygonal model. In order to detect potential colliding set(PCS) of prism between two polygonal models in a unit time, we apply the visibility test based on the occlusion query to two sets of prisms which are defined from two polygonal models in a unit time. Moreover, we execute the narrow band culling based on SAT(Separating Axis Test) to define potential colliding prism pairs from PCS of prisms extracted as a result of the visibility test. In the SAT, we examine one axis to be perpendicular to a plane which divides a 3D space into two half spaces to include each prism. In the experiments, we applied the proposed culling method to pairs of polygonal models with the different size and compared the number of potential colliding prism pairs with the number of all possible prism pairs of two polygonal models. We also compared effectiveness and performance of the visibility test-based method with those of the SAT-based method as the second narrow band culling. In an experiment using two models to consist of 2916 and 2731 polygons, respectively, we got potential colliding prism pairs with 99 % of culling rate.

• Journal of the Korea Computer Graphics Society
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• v.6 no.1
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• pp.11-17
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• 2000

We present collision-handling method that includes self-penetration in the case of the colliding between rigid and deformable objects. The collision between objects is detected through the overlap test to the hierarchical structures of the objects. For detecting the collision between the objects at in-between frame, we try overlap test using the structures of a dummy and the rigid objects in addition to the test between the rigid and deformable objects. The dummy object is made from the rigid objects moving direction. When collision occurs, a deformable object must be deformed, as the object doesn't permit penetration. Self-penetration may occur during the object is deformed. It is rapidly detected between the object and a dummy object of another type. The dummy object is made from the object's deformation area between two continuous frames. We constrain the object is deformed until it is self-contacted. Our method can be applied without concerning of the shape of a object.

• Journal of the Korean Society of Marine Environment & Safety
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• v.20 no.2
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• pp.202-209
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• 2014

In this paper, a developed device for detecting target's location and avoiding collision is proposed. Velocity and acceleration model of target are derived to estimate target's information, i.e. position, velocity and acceleration considering process and measurement noise. Kalman filtering method applied to the estimation process and its results was confirmed by simulation. The distance measurements system using laser sensor for moving target system is also developed to confirm the effectiveness of the proposed scheme. Experiments to get information of moving target with velocity and acceleration model was executed. The data with filtering and without filtering was compared by experiments. Discontinuous measured data was changed to smooth and continuous data by Kalman filtering. It is confirmed that desired data was obtained by applying proposed scheme. UI for measuring and monitoring the target data is developed and visual and auditory alarm function is attached on the system Finally, position estimation system of moving target with good performance is achieved by low price equipments.

• Proceedings of the KSR Conference
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• 1999.05a
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• pp.307-314
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• 1999

The potential use of ranging sensors for reducing the occurrence of accidents in real environment is explored by many companies and laboratories. Most of the sensors under investigation utilize the FMCW(Frequency Modulated Continuous Wave) waveforms. The automotive environment presents to the FMCW radar sensor a multitude of moving and fixed targets and the sensor must detect and track only the targets which may pose a threat of collision or passengers accident. The sensor must function accurately in the presence of background echoes generated by moving and fixed targets, ground reflections, atmospheric noises, including rains, fog, and, snow and noise generated within the receiver. False detection of the desired target in this environment may issue false alarms. That may be dangerous to the passenger and the vehicle. A high false alarm rate is totally unacceptable. The false alarm mechanism consists of noise peaks, crossing the threshold and the undesired response of the system to off lane targets which are not potentially hazardous to the radar equipped vehicle. This paper presents an improve technique safety performance for driver-less operation using FMCW radar sensors.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.890-893
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• 2014

In this paper, we present a signal processing algorithm for a marine radar system, in which the evaluation of probability of collision as well as target detection and tracking are performed. Moreover, the digital signal processor that implements the algorithm is proposed. As simulation environment, a mechanically scanning antenna utilizing FMCW signal is used, conducting the beamforming operation with 1 degrees intervals. Test board consists of DSP chips and FPGA, which enable the implemented system to operate in real-time.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.01a
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• pp.395-398
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• 2023

본 논문에서는 물리 기반 옷감 시뮬레이션과 SPH(Smoothed particle hydrodynamics) 기반의 유체 시뮬레이션 간의 상호작용에서 표현되는 다양한 물리적 효과를 GPU 기반으로 빠르게 표현할 수 있는 프레임워크를 제안한다. 기존 기법과는 다르게 수치적 안정성을 개선하기 위해 CCD(Continuous collision detection)를 활용하였으며, 모든 연산이 GPU에서 동작하기 때문에 매우 빠르게 옷감과 유체의 상호작용 장면인 다공성 재질, 기공 흐름, 흡수, 방사, 확산을 모델링할 수 있다.