• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.297-298
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• 2006

In this paper, we propose a real-time surveillance system for security of important area such as military bases, prisons, and strategic infra structures. The proposed system recognizes the movement of objects in dark environments. First, the Multi-scale retinex (MSR) is processed to enhance the contrast of image captured in dark environments. Then, the enhanced input image is subtracted with the background image. Finally, each bounding box enclosing each objects are tracked. The center point of each bounding box obtained by the proposed algorithm provides more accurate tracking information. Experimental results show that the proposed system provides good performance even though an object moves very fast and the background is quite dark.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.11a
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• pp.459-460
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• 2011

본 논문에서는 이러한 방식에서 탈피한, 3D 그래픽을 이용한 1인칭 미니 회피게임을 제작하는 방법에 대해 제안한다. 기존의 3인칭 시점에 상하좌우 네 방향으로만 움직이는 방식을 벗어나, 시점을 1인칭으로 변환하고 FPS와 같은 시점과 이동방식을 제공하며, 기존의 2D게임에서 사용되던 축이 고정된 오브젝트의 충돌인 AABB(Axis Aligned Bounding Box)가 아닌 축이 수시로 변하는 OBB(Oriented Bounding Box) 방식을 사용함으로 써, 3D 그래픽에서도 2D 그래픽에서처럼 정교한 충돌 검출 기능이 가능하도록 제작한다.

• Journal of the Korea Society of Computer and Information
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• v.14 no.8
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• pp.43-50
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• 2009

Text information in a digital video provides crucial information to acquire semantic information of the video. In the proposed method. text candidate regions are extracted from input sequence by using characteristics of stroke and text candidate regions are localized by using projection to produce text bounding boxes. Bounding boxes containing text regions are verified geometrically and each bounding box existing same location is tracked by calculating matching measure. which is defined as the mean of absolute difference between bounding boxes in the current frame and previous frames. Finally. text regions are enhanced using temporal redundancy of bounding boxes to produce final results. Experimental results for various videos show the validity of the proposed method.

• Journal of the Korea Computer Graphics Society
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• v.13 no.4
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• pp.21-27
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• 2007

The 3D Delaunay triangulation is the most widely used method for the mesh creation via the triangulation of a 3D point cloud. However, the method involves a heavy computational cost and, hence, in many interactive applications, it is not appropriate for surface triangulation. In this paper, we propose an efficient triangulation method to create a surface mesh from a 3D point cloud. We divide a set of object points into multiple subsets and apply the 2D Delaunay triangulation to each subset. A given 3D point cloud is cut into slices with respect to the OBB(Oriented Bounding Box) of the point set. The 2D Delaunay triangulation is applied to each subset producing a partial triangulation. The sum of the partial triangulations constitutes the global mesh. As a postprocessing process, we eliminate false edges introduced in the split steps of the triangulation and improve the results. The proposed method can be effectively applied to various image-based modeling applications.

• Journal of the Korea Society of Computer and Information
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• v.28 no.1
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• pp.93-101
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• 2023

In this paper, we propose a method of creating a 3D bounding box for an object using a vanishing point to increase the accuracy of object recognition in an image when recognizing an traffic object using a video camera. Recently, when vehicles captured by a traffic video camera is to be detected using artificial intelligence, this 3D bounding box generation algorithm is applied. The vertical vanishing point (VP1) and horizontal vanishing point (VP2) are derived by analyzing the camera installation angle and the direction of the image captured by the camera, and based on this, the moving object in the video subject to analysis is specified. If this algorithm is applied, it is easy to detect object information such as the location, type, and size of the detected object, and when applied to a moving type such as a car, it is tracked to determine the location, coordinates, movement speed, and direction of each object by tracking it. Able to know. As a result of application to actual roads, tracking improved by 10%, in particular, the recognition rate and tracking of shaded areas (extremely small vehicle parts hidden by large cars) improved by 100%, and traffic data analysis accuracy was improved.

• Land and Housing Review
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• v.14 no.4
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• pp.95-102
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• 2023

Numerous investigations have explored the integration of machine leaning algorithms with high-resolution drone image for object detection in urban settings. However, a prevalent limitation in vehicle extraction studies involves the reliance on bounding boxes rather than instance segmentation. This limitation hinders the precise determination of vehicle direction and exact boundaries. Instance segmentation, while providing detailed object boundaries, necessitates labour intensive labelling for individual objects, prompting the need for research on automating unsupervised instance segmentation in vehicle extraction. In this study, a novel approach was proposed for vehicle extraction utilizing unsupervised SVM classification applied to vehicle bounding boxes in drone images. The method aims to address the challenges associated with bounding box-based approaches and provide a more accurate representation of vehicle boundaries. The study showed promising results, demonstrating an 89% accuracy in vehicle extraction. Notably, the proposed technique proved effective even when dealing with significant variations in spectral characteristics within the vehicles. This research contributes to advancing the field by offering a viable solution for automatic and unsupervised instance segmentation in the context of vehicle extraction from image.

• Journal of Information Processing Systems
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• v.8 no.4
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• pp.713-720
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• 2012

Unlike FEM (Finite Element Method), which provides an accurate deformation of soft objects, FFD (Free Form Deformation) based methods have been widely used for a quick and responsive representation of deformable objects in real-time applications such as computer games, animations, or simulations. The FFD-AABB (Free Form Deformation Axis Aligned Bounding Box) algorithm was also suggested to address the collision handling problems between deformable objects at an interactive rate. This paper proposes an enhanced FFD-AABB algorithm to improve the frame rate of simulation by adding the bounding sphere based collision test between 3D deformable objects. We provide a comparative analysis with previous methods and the result of proposed method shows about an 85% performance improvement.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.05a
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• pp.1329-1330
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• 2010

• Korean Journal of Computational Design and Engineering
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• v.16 no.3
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• pp.178-186
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• 2011

Static CAD models are the CAD models that do not have feature information and modeling history. These static models are generated by translating CAD models in a specific CAD system into neutral formats such as STEP and IGES. When a CAD model is translated into a neutral format, its precious feature information such as feature parameters and modeling history is lost. Once the feature information is lost, the advantage of feature based modeling is not valid any longer, and modification for the model is purely dependent on geometric and topological manipulations. However, the capabilities of the existing methods to modify static CAD models are limited, Direct modification methods such as tweaking can only handle the modifications that do not involve topological changes. There was also an approach to modify static CAD model by using volume decomposition. However, this approach was also limited to modifications of protrusion features. To address this problem, we extend the volume decomposition approach to handle not only protrusion features but also depression features in a static CAD model. This method first generates the model that contains the volume of depression feature using the bounding box of a static CAD model. The difference between the model and the bounding box is selectively decomposed into so called the feature volume and the base volume. A modification of depression feature is achieved by manipulating the feature volume of the static CAD model.

• International Journal of Precision Engineering and Manufacturing
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• v.9 no.4
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• pp.79-82
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• 2008

A method is described for ideally reconstructing the profile from a surface profiling measurement containing a reasonable amount of null measurement data. The proposed method can conjecture lost information and rectify irregular data that result due to bad measuring environments, signal transmission noise, or instrument-induced errors, The method adopts the concept of computer graphics and consists of several processing steps. First, a search for valid data in the neighborhood of the null data is performed. The valid data are then grouped and their contours are extracted. By analyzing these contours, a bounding box can be obtained and the general distribution of the entire area encompassing the valid and null data is determined Finally, an ideal surface model is overlaid onto the measurement results based on the bounding box, generating a complete reconstruction of the calculations, A surface-profiling task on a liquid crystal display photo spacer is used to verify the proposed method. The results are compared to those obtained through the use of a scanning electron microscope to demonstrate the accuracy of the proposed method.