Perceptual Modeling and Reproduction of Gloss

The reproduction of gloss on displays is generally not based on perception and as a consequence does not guarantee the best visualization of a real material. The reproduction is composed of four different steps: measurement, modeling, rendering, and display. The minimum number of measurements required to approximate a real material is unknown. The error metrics used to approximate measurements with analytical BRDF models are not based on perception, and the best visual approximation is not always obtained. Finally, the gloss perception difference between real objects and objects seen on displays has not sufficiently been studied and might be influencing the observer judgement. This thesis proposes a systematic, scalable, and perceptually based workflow to represent real materials on displays. First, the gloss perception difference between real objects and objects seen on displays was studied. Second, the perceptual performance of the error metrics currently in use was evaluated. Third, a projection into a perceptual gloss space was defined, enabling the computation of a perceptual gloss distance measure. Fourth, the uniformity of the gloss space was improved by defining a new gloss difference equation. Finally, a systematic, scalable, and perceptually based workflow was defined using cost-effective instruments

Measuring perceived gloss of rough surfaces

This thesis is concerned with the visual perception of glossy rough surfaces, specifically those characterised by 1/fB noise. Computer graphics were used to model these natural looking surfaces, which were generated and animated to provide realistic stimuli for observers. Different methods were employed to investigate the effects of varying surface roughness and reflection model parameters on perceived gloss. We first investigated how the perceived gloss of a matte Lambertian surface varies with RMS roughness. Then we estimated the perceived gloss of moderate RMS height surfaces rendered using a gloss reflection model. We found that adjusting parameters of the gloss reflection model on the moderate RMS height surfaces produces similar levels of gloss to the high RMS height Lambertian surfaces. More realistic stimuli were modelled using improvements in the reflection model, rendering technique, illumination and viewing conditions. In contrast with previous research, a non-monotonic relationship was found between perceived gloss and mesoscale roughness when microscale parameters were held constant. Finally, the joint effect of variations in mesoscale roughness (surface geometry) and microscale roughness (reflection model) on perceived gloss was investigated and tested against conjoint measurement models. It was concluded that perceived gloss of rough surfaces is significantly affected by surface roughness in both mesoscale and microscale and can be described by a full conjoint measurement model

Realistic visualisation of cultural heritage objects

This research investigation used digital photography in a hemispherical dome, enabling a set of 64 photographic images of an object to be captured in perfect pixel register, with each image illuminated from a different direction. This representation turns out to be much richer than a single 2D image, because it contains information at each point about both the 3D shape of the surface (gradient and local curvature) and the directionality of reflectance (gloss and specularity). Thereby it enables not only interactive visualisation through viewer software, giving the illusion of 3D, but also the reconstruction of an actual 3D surface and highly realistic rendering of a wide range of materials. The following seven outcomes of the research are claimed as novel and therefore as representing contributions to knowledge in the field: A method for determining the geometry of an illumination dome; An adaptive method for finding surface normals by bounded regression; Generating 3D surfaces from photometric stereo; Relationship between surface normals and specular angles; Modelling surface specularity by a modified Lorentzian function; Determining the optimal wavelengths of colour laser scanners; Characterising colour devices by synthetic reflectance spectra

Towards Predictive Rendering in Virtual Reality

The strive for generating predictive images, i.e., images representing radiometrically correct renditions of reality, has been a longstanding problem in computer graphics. The exactness of such images is extremely important for Virtual Reality applications like Virtual Prototyping, where users need to make decisions impacting large investments based on the simulated images. Unfortunately, generation of predictive imagery is still an unsolved problem due to manifold reasons, especially if real-time restrictions apply. First, existing scenes used for rendering are not modeled accurately enough to create predictive images. Second, even with huge computational efforts existing rendering algorithms are not able to produce radiometrically correct images. Third, current display devices need to convert rendered images into some low-dimensional color space, which prohibits display of radiometrically correct images. Overcoming these limitations is the focus of current state-of-the-art research. This thesis also contributes to this task. First, it briefly introduces the necessary background and identifies the steps required for real-time predictive image generation. Then, existing techniques targeting these steps are presented and their limitations are pointed out. To solve some of the remaining problems, novel techniques are proposed. They cover various steps in the predictive image generation process, ranging from accurate scene modeling over efficient data representation to high-quality, real-time rendering. A special focus of this thesis lays on real-time generation of predictive images using bidirectional texture functions (BTFs), i.e., very accurate representations for spatially varying surface materials. The techniques proposed by this thesis enable efficient handling of BTFs by compressing the huge amount of data contained in this material representation, applying them to geometric surfaces using texture and BTF synthesis techniques, and rendering BTF covered objects in real-time. Further approaches proposed in this thesis target inclusion of real-time global illumination effects or more efficient rendering using novel level-of-detail representations for geometric objects. Finally, this thesis assesses the rendering quality achievable with BTF materials, indicating a significant increase in realism but also confirming the remainder of problems to be solved to achieve truly predictive image generation

Characterization and visualization of reflective properties of surfaces

Images play a vital role in several fields of natural science research, including biology, physics, astrophysics, and computer science. In the natural sciences, images are commonly used in measurements or documentation; such applications include images made with telescopes, optical microscopes, or electron microscopes. In the humanities, images also play an important role in research. In art history, for example, many different types of images, from photos of small objects to three-dimensional reconstructions of buildings, help art historians to develop theories, to discuss them with other scholars, and to document the current state of artworks, e.g. in the process of restoration. This is particularly useful if the object is not easily accessible, in which case a common solution is to work with photographs. Digital photography has simplified the process of visual representation, because digital images can be easily shared and made accessible. However, when it comes to more complex kinds of artworks like mosaics, these static and two-dimensional images are not able to reproduce the actual visual impression of the object. Similar considerations apply to a variety of other artifacts, such as early prints, books, parchments, and textiles. The challenge in the digitization of of these objects lies in their complex surface properties and reflection behavior. A promising way to solve those limitations is the use of Reflectance Transformation Imaging. RTI is a set of computational photographic methods that capture a subject’s surface shape and color, making it possible to interactively re-light the subject from any direction by means of a mathematical model. The major drawback of RTI is the limitation of the applied mathematical model. Other drawbacks are the RTI imaging workflow and the fact that display of RTI requires a particular stand-alone application. In this thesis, the author developed a data-driven scientific approach to reproduce surfaces composed of lambertian and glossy materials using the RTI technique with as few parameters as possible. This new approach has been called eRTI (enhanced Reflection Transformation Imaging). Furthermore the hardware needed to acquire RTI and eRTI has been improved, by collaborating with a local Swiss firm to develop a novel solution for image acquisition. Lastly a web-based viewer has been developed, to render eRTI images in any standard web browser, even on most mobile devices. The qualities of eRTI have been tested using a novel approach that includes a quantitative and a qualitative method. The results show agreement between the techniques