基于空间聚类增强Lightcuts的光照计算  

Enhancing Illumination Computation of Lightcuts with Spatial Coherence

作　　者：王光伟[1,2] 谢国富[1,2] 王文成[1] 

机构地区：[1]中国科学院软件研究所计算机科学国家重点实验室,北京100190 [2]中国科学院大学,北京100049

出　　处：《计算机学报》2013年第11期2364-2370,共7页Chinese Journal of Computers

基　　金：国家自然科学基金(61379087);中国科学院知识创新工程领域前沿项目资助~~

摘　　要：Lightcuts是面向多光源场景的高效绘制方法.它渐进地对光源进行聚类组织,并以二叉树进行管理,由此在绘制时可用一些光源聚类的代表光源(统称为‘光源割’)进行光照计算,以减少需要计算的光源数量.但是,当光源很多并分布复杂时,在二叉树结构中寻找光源割也要花费不少的计算.为此,有些方法提出利用绘制中的图像连贯性来减少光源割的搜寻计算,并取得了较好的效果.文中提出利用空间聚类来减少光源割的搜寻计算,即先根据位置和法向对场景中的几何位置进行聚类,为各个类的代表点寻找其光源割,以作为该类其它点搜索各自对应光源割的初始情况.实验表明,文中方法能很好地减少光源树中搜索光源割的计算,提高Lightcuts的光照计算效率,优于利用图像连贯性的加速方法,加速性能稳定,并且光源越多分布越复杂,加速效果越好.Lightcuts is an efficient rendering algorithm for scenes with many complex lights. In order to approximate lights by representative lights of some clusters （defined as a cut）, lightcuts builds a binary light tree to progressively cluster the lights. As a result, the number of lights to be processed is reduced during rendering. However, when dealing with plenty of complex lights, finding cuts in a light tree is still expensive. Therefore some algorithms exploit image coherence to accelerate cuts computation and achieve good performance. This paper proposes an algorithm that exploits spatial coherence to reduce the search cost of cuts. The proposed method clusters geometry positions by their material and normal. For each cluster, the proposed method first cal culates the cut of the representative point of the cluster, and then uses the cut as the initial to search for the cuts of other points in this cluster. Experimental results show that the new method can significantly reduce the cost of finding cuts in light tree, enhance illumination computation and outperform other methods using image coherence, with stable effect on acceleration. In general, with more lights in a more complex distribution, the new method can achieve more acceleration.

关 键 词：光照计算 Lightcuts 空间聚类 多光源 真实感绘制 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]