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Ray Tracing-based Real-time Collision Detection Using Bounding Mesh of Polygonal Model
Seokyoung Koh, Youngwook Kim, Insung Ihm
http://doi.org/10.5626/JOK.2024.51.2.173
For accurate real-time collision detection between two polygonal meshes, it is essential to check if each triangle of one polygonal mesh is intersected with the other polygonal mesh. However, because the number of triangles of large-size meshes easily increases, such a simple method often cannot achieve real-time detection. In this paper, we propose a GPU-assisted real-time collision detection technique where both a bounding mesh approximating a given large-size mesh and the GPU-assisted ray-tracing hardware are effectively exploited. In this method, the bounding mesh that intends to reduce the number of triangles participating in the triangle-object intersection is first intersected with the other mesh. In this way, it was possible to perform the collision detection operation within the reduced region with decreased numbers of triangles. In addition, we improved the performance of the collision detection process by exploiting the GPU-supported ray-tracing engine for accelerating the triangle-object intersection operation.
Development of an Information Extraction System Using the Dependency Analysis
Hyeyoung Kim, Hangyeol Sun, Youngwook Kim
http://doi.org/10.5626/JOK.2020.47.3.266
In this paper, we propose an information extraction system that can automatically extract user intended key syntax, by analyzing the dependency parse of a sentence. Previous Open Information Extraction studies extract two related arguments based on a verb to structuralize information, from massive data in unsupervised methods. However, users may be unable to extract key syntax accordingly, from a sentence without a verb or a sentence with various arguments. To solve this problem, this system first splits a sentence into an appropriate length to enhance the accuracy of analysis and incorporates dependency relations between words using a dependency parser. Then, we defined four extraction rules from the most basic sentence structures and built a system to extract meaningful chunking from predefined rules. Consequently, with a rule-based approach, users can freely add or modify extraction rules and derive key syntax from any type of a document. We experimented with Wikipedia data and the system achieved 33% more accuracy than DepOE, another OIE system that applies a dependency parser. As a result of the experiment, the system we propose enables easy analyses of written text and will be useful in analyzing various texts in the future.
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