High Quality and Low Data Storage Repeat Pattern Normal Map

碩士 === 國立臺灣科技大學 === 資訊工程系 === 107 === 3D models are mainly used in console games and movie industries, but recently, with the significant increase of computing performance, are also used on mobile devices. Simultaneously, many rendering methods are introduced to save the data storage and computation...

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Bibliographic Details
Main Authors: Yan-Lin Chen, 陳彥霖
Other Authors: Yu-Chi Lai
Format: Others
Language:zh-TW
Published: 2019
Online Access:http://ndltd.ncl.edu.tw/handle/7537xf
Description
Summary:碩士 === 國立臺灣科技大學 === 資訊工程系 === 107 === 3D models are mainly used in console games and movie industries, but recently, with the significant increase of computing performance, are also used on mobile devices. Simultaneously, many rendering methods are introduced to save the data storage and computation of 3D models, and our research is related to normal mapping.Using raster images to store the normal difference on high-polygon 3D models and texturing to low-polygon 3D models can get a result that visually close enough to high-polygon 3D models.Repeat pattern normal maps contain repeat information, result in huge data storage and the aliasing become severe depend on the repeat times.Even with 2K resolution texture, the aliasing in render result is still obvious when zoomed in. In our study, we found that repeat patterns grow directions are similar to skeleton's.Nearby patterns' shape, direction, size are similar.In order to save data storage of huge amount of repeat pattern,we generate texture coordinate by using skeleton-based 4-RoSy flow field and repeat pattern start position, density to place patterns.Also, we design a method to vectoring normal map, to solve the problem of traditional raster image resolution limitation and aliasing problems.Our research propose a method to vectoring normal maps by using diffusion curves, which can use less data to represent the smooth areas of the images, then calculate the difference of pixels by using normal rotation quaternions.Normal rotation quaternions are better at reserving the detail information than traditional color differential method, and can precisely find positions of larger difference of normal.Therefore, our research can produce diffusion curves qualify the normal difference, and then use green function to compute the color on each side of diffusion curves.Besides, traditional normal map generated methods are complicating, and it is hard to modify once the normal map is produced.And diffusion curves are convenient to be modified.We design a method to measure the error of normal map reconstruction result by using quaternions rotation angle difference and then calculate PSNR and compare data storage of our method with input data storage.Our research reduce huge amount of data storage and remains high quality.We combine diffusion curve vectoring method and texture coordinate generation method based on flow field, to reduce the data storage.