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Skin Texture Modeling 总被引:1,自引:0,他引:1
Cula Oana G. Dana Kristin J. Murphy Frank P. Rao Babar K. 《International Journal of Computer Vision》2005,62(1-2):97-119
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Visual prototyping of materials is relevant for many computer graphics applications. A large amount of modelling flexibility can be obtained by directly rendering micro‐geometry. While this is possible in principle, it is usually computationally expensive. Recently, bidirectional texture functions (BTFs) have become popular for efficient photorealistic rendering of surfaces. We propose an efficient system for the computation of synthetic BTFs using Monte Carlo path tracing of micro‐geometry. We observe that BTFs usually consist of many similar apparent bidirectional reflectance distribution functions. By exploiting structural similarity we can reduce rendering times by one order of magnitude. This is done in a process we call non‐local image reconstruction, which has been inspired by non‐local means filtering. Our results indicate that synthesizing BTFs is highly practical and may currently only take a few minutes for BTFs with 70 × 70 viewing and lighting directions and 128 × 128 pixels. 相似文献
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程飞 《安徽电子信息职业技术学院学报》2007,6(5):118-119
本文结合NURBS曲面和BTF术的基本原理,探讨了二者的结合在真实感图形绘制上的具体应用,并给出了具体算法. 相似文献
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织物的过程化双向纹理函数生成算法 总被引:3,自引:0,他引:3
针对编织式样具有近似规则的微观几何结构这一特点,提出了一种基于织物几何中结构建模的过程化双向纹理函数生成算法.首先从分析编织式样的结构人手,得出编织式样变形的基本单元——可见丝线段;然后通过对其进行数学建模并按编织式样进行组合,产生了织物的几何中结构;最后利用光线跟踪算法实现了编织式样在不同光照和视线条件下的纹理外观,从而生成织物的双向纹理函数纹理. 相似文献
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In multi-camera video tracking, the tracking scene and tracking-target appearance can become complex. To finish multi-camera tracking in these challenging, we first utilize an improved brightness transfer function to establish matching tasks of different cameras and to reduce the influence of brightness changes between multiple cameras. Then, we proposes an improved colour-texture feature fusion (ICTFF) that is composed of the colour features and texture features for multi-camera human tracking in non-overlapping field of view. It’s the first time to use artificial immune random forest with fully exploit the linear combination information of the feature and colour feature that can achieving the optimization of the number of decision trees and the effective classification of the target feature. Compared with state-of-the-art algorithms, our ICTFF algorithm can significantly improve the tracking accuracy in some complex scenes, such as changing the speed, changing the direction and appearance of the target. 相似文献