Simulating the Oil Painting in an NPR 3D Animation System
| Autor: | Jun-Lan Yang, 楊竣蘭 |
|---|---|
| Rok vydání: | 2008 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 96 Non-Photorealistic Rendering (NPR) has been an important issue in the field of Computer Graphics. Instead of highlighting the realism of CG synthesized images, NPR focus on the representation of the stroke and paint style. One of the most important features of Non-Photorealistic Rendering is the exaggeration expression over the subjects of image. Therefore, NPR is suitable to synthesize images that simulate the paint style with the visual effect of strokes. The research issues of NPR can be roughly divided into two types, 2D image-based method and 3D model-based method. In this paper, we synthesize 3D model-based NPR images and animation with continuous volumetric strokes to simulate the visual effects of oil painting. According to our survey on oil paintings, we conclude that the heap of pigment and the volumetric property of each single stroke are two of the most important factors in the works of oil painting. According to the distance from the strokes to the edge of the object, we set up the priority of all strokes. Based on the order, through dynamically segmenting the canvas apart, we make the grouping with regional stroke in the object. And then pile strokes in the same group. The information of the thickness of strokes is stored in a Z-buffer-like data structure. The 3D canvas is then rendered based on this information. Main contribution of this research includes producing the volumetric strokes, and simulating the oil color correctly on the canvas. These goals are achieved by piling up the strokes on the same pixel, and superposing the pigments to simulate the final resulted color on the canvas. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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