变化光照的对象图像合成

光照是真实感图形绘制和许多图像应用中的一个非常重要的因素.提出了一种完全基于图像的方法来反映光照变化在绘制对图像时的影响.所提出的方法不是直接去估计对象反射模型中的参数,或是去拟合BRDF函数,而是用奇异值分解(SVD)来拟合Lambertian 对象在光照和几何朝向变化情况下的所有图像集合.其中,光线方向的解析表达可以由样本图像、基图像以及已知类对象的图像集导出,对象在新的光线方向下的图像可通过适当地线性组合基图像而有效地绘出.另外,利用对SVD系数的线性插值可以生成反映对象几何朝向和光线变化的连续变形

Object Image Synthesis under Changing of Illumination

Illumination is an important aspect in realistic graphics rendering and most image related applications. The paper proposes a pure image based rendering method to synthesis the variation of illumination impacted on an object. Rather than estimating the BRDF function or any parameters in a reflectance model, Singular Value Decomposition (SVD) is used to estimate a low dimensional approximation of the image set of a Lambertian object under both changing of illumination and geometrical pose. In the method, light directions are analytically derived from the samples and the base images as well as images with known of the class of the objects. Images with any novel lighting directions can be rendered very efficiently by properly linear combination of the base images. Smooth morphing sequence of lighting and pose variation can be generated by linear interpolation of the SVD coefficients. A feature of this method is that it supplies a simple and compact way to represent dataset and synthesize novel images, which lends it to be suitable for many image-based applications.