Marjan Shahpaski
The appearance of objects is governed by how they reflect, transmit and absorb the light they receive. That, in turn, depends on the material's internal structure, surface structure, and viewing and illumination directions. Changes in those characteristics can produce dramatic shifts in a material's appearance.
In this thesis, we explore how the optical properties can be estimated accurately using computational imaging. Current solutions are based on using instruments that are on the expensive side, such as spectrophotometers, profilometers and goniophotometers; hence, we explore the use of more affordable equipment, such as cameras. We start with the reflected light, and how the surface structure and roughness can be measured with commodity hardware such as projectors and cameras. We continue to the transmitted light, where we study methods for measuring hemispherical and directional transmittance.
Systems based on the projection of structured light can be used for high-precision depth estimation. These methods provide non-contact means of depth estimation by using a calibrated camera-projector pair. Calibration of such systems is a cumbersome and time-consuming task. We, thus, present a novel method that allows for simultaneous geometric and radiometric calibration of a projector-camera pair. We leverage the different colorimetric properties of the printed and projected patterns to perform the geometric calibration, and perform the radiometric calibration of the projector with the information contained inside the projected squares. We show that our method performs on par with current approaches that all require separate geometric and radiometric calibration. We then apply the algorithm to calibrate a structured light system with the goal of surface structure estimation of nearly planar surfaces. The surface structure is then used to calculate their macroscopic surface roughness. Over a set of samples, our results are comparable to those from a high-grade commercial profilometer.
The accurate measurement of transmittance properties of materials is essential in the printing and display industries to ensure accurate color reproduction. We explore different measurement geometries for total transmittance, and show that the measurements are highly affected by the geometry used, since certain geometries can introduce a measurement bias. We build a flexible custom setup that can simulate these geometries, and evaluate it qualitatively and quantitatively. We also compare its measurements to those of widely used commercial solutions, and show that significant differences exist over our test set. These findings stress the importance of including the measurement geometry when reporting total transmittance.
The BSDF is of great importance in many applications, from rendering and visual special effects to architectural modelling of illumination. We propose a novel design for the measurement of BSDF, more specifically the BTDF. It is based on radial catadioptric imaging, where we illuminate the measured sample with a collimated beam of light, the emerging light on the other side of the sample is collected by a diffusing cylinder, and a camera registers the steady-state radiance. After inverting the light transport inside the cylinder, we can compute the sample's BTDF. In simulations, our proposed design achieves results that are well aligned with the ground truth, for both smooth and high-frequency BTDFs that feature sharp intensity changes.
EPFL2020
