Reflectance Transformation Imaging Method for Large-Scale Objects

Abstract

RTI is an image-based rendering method which can represent the appearance of an object under varying illuminations. To create realistic synthetic-images using RTI, it is necessary to take dozens of images on a mounted camera with a calibrated point light source. Conventional RTI methods have proposed complex lighting systems in a hemispherical dome, or manually calibrate light poses using a reflective probe. In most cases, those methods are not suitable for the large-scale object in an outdoor environment because the size of the target object is restricted by the configuration of measurement systems. In this paper, we present a new RTI method which can create photorealistic images of a large scale outdoor scene under arbitrary light directions. Instead of capturing RTI samples at a time for an entire domain, we divide the RTI domain into a set of subsections. RTI samples in each section are acquired using a camera and an uncalibrated light source. After acquiring samples, we estimate svBRDF of measured samples without any prior knowledge of a 3D model, light poses, and surface normals. We also present an approach to merge the partial RTI images into a panoramic image. Experimental results show that our framework can extend the RTI methods applicable to large-scale objects.