Adaptive Measurement of Material Appearance

One of the ultimate challenges of computer graphics is the realistic visualization of appearance of real-world materials. The appearance can be captured by various approaches, but they are often only approximative or usually require an excessively long measurement time. Therefore, this thesis deals with the precise measurement of material appearance utilizing time-reducing adaptive methods. We propose an affordable setup for its instantaneous analysis that is based on an ellipsoidal reflector. Also, we study a human's ability to distinguish structure of a material in a virtual environment in dependence on an observation distance. We study the optimal deployment of the signals and propose an interpolation method that enables a quick reconstruction of an arbitrary value. Next, we introduce adaptive approaches that rely on the database. Our template-based methods use precomputed sampling patterns for the measurement of a new material and they achieve better results than conventional methods for more than several hundred samples.