Hertzmann Aaron, Seitz Steven M
Computer Science Department, University of Toronto, 10 King's College Road, Room 3302, Toronto, ON M5S 3G4 Canada.
IEEE Trans Pattern Anal Mach Intell. 2005 Aug;27(8):1254-64. doi: 10.1109/TPAMI.2005.158.
This paper presents a technique for computing the geometry of objects with general reflectance properties from images. For surfaces with varying material properties, a full segmentation into different material types is also computed. It is assumed that the camera viewpoint is fixed, but the illumination varies over the input sequence. It is also assumed that one or more example objects with similar materials and known geometry are imaged under the same illumination conditions. Unlike most previous work in shape reconstruction, this technique can handle objects with arbitrary and spatially-varying BRDFs. Furthermore, the approach works for arbitrary distant and unknown lighting environments. Finally, almost no calibration is needed, making the approach exceptionally simple to apply.
本文提出了一种从图像中计算具有一般反射特性的物体几何形状的技术。对于具有不同材质属性的表面，还会计算出对不同材质类型的完整分割。假设相机视角固定，但光照在输入序列中会发生变化。还假设一个或多个具有相似材质和已知几何形状的示例物体在相同光照条件下成像。与之前大多数形状重建工作不同，该技术可以处理具有任意和空间变化的双向反射分布函数（BRDF）的物体。此外，该方法适用于任意远距离和未知的光照环境。最后，几乎不需要校准，使得该方法应用起来异常简单。
