• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.177-180
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• 2005

Three dimensional shaded images are standard visualization method for CAD models on the computer screen. Therefore, much of the effort in the visualization of CAD models has been focused on how conveniently and realistically CAD models can be displayed on the screen. However, shaded 3D CAD data images captured from the screen may not be suitable for some application areas. Technical document, either in the paper or electronic form, can more clearly describe the shape and annotate parts of the model by using projected 2D line drawing format viewed from a user defined view direction. This paper describes an efficient method for generating such a 2D line drawing data in the vector format. The algorithm is composed of silhouette line detection, hidden line removal and cleaning processes.

• Korean Journal of Computational Design and Engineering
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• v.11 no.6
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• pp.455-463
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• 2006

Hidden line removal(HLR) algorithms can be devised either in the image space or in the object space. This paper describes a hidden line removal algorithm in the object space specifically for the CAD viewer data. The approach is based on the Appel's 'Quantitative Invisibility' algorithm and fundamental concept of 'back face culling'. Input data considered in this algorithm can be distinguished from those considered for HLR algorithm in general. The original QI algorithm can be applied for the polyhedron models. During preprocessing step of our proposed algorithm, the self intersecting surfaces in the view direction are divided along the silhouette curves so that the QI algorithm can be applied. By this way the algorithm can be used for any triangulated freeform surfaces. A major advantage of this algorithm is the applicability to general CAD models and surface-based visualization data.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.4
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• pp.433-438
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• 2009

In this paper, we propose the robust features extraction method of human by using the skeleton model and hybrid silhouette model. The proposed feature extraction method is divided by hands, shoulder line and elbow region extraction. We use the peer's color information to find the position of hands and propose the circle detection method to extract the shoulder line and elbow. Finally, we show the effectiveness and feasibility of the proposed method through some experiments.