Adaptive view and illumination planning for SVBRDF measurement of complicated three-dimensional objects

Abstract

Appearance attributes of a three-dimensional (3-D) object, including reflection and color, are modeled as a spatially varying bidirectional reflectance distribution function (SVBRDF). However, a considerable number of images of the object are required to accurately define an SVBRDF when it exhibits complicated geometric components, thereby leading to a considerable amount of time to acquire, store, and process them. We propose a method to considerably decrease the number of images for SVBRDF modeling while maintaining the quality of the model that is achieved with several images. We introduce an acquisition score and its corresponding objective function by considering the local geometry and reflectance properties to estimate the optimal view and illumination directions for the image acquisition in which an object is measured with a reduced number of images. The captured images are subsequently processed to obtain an SVBRDF of the object. The experimental results demonstrate that the proposed method measures the appearance of a 3-D object with complicated shapes by using a few hundred images and efficiently produces an SVBRDF of the object with complicated shapes. The results indicate that the proposed method photorealistically renders an object with fewer artifacts than existing methods when any arbitrary view and illumination directions are given.