Jiří Filip

Bidirectional Texture Function Modeling: A State of the Art Survey

An ever-growing number of real-world computer vision applications require classification, segmentation, retrieval, or realistic rendering of genuine materials. However, the appearance of real materials dramatically changes with illumination and viewing variations. Thus, the only reliable representation of material visual properties requires capturing of its reflectance in as wide range of light and camera position combinations as possible. This is a principle of the recent most advanced texture representation, the bidirectional texture function (BTF). Multispectral BTF is a seven-dimensional function that depends on view and illumination directions as well as on planar texture coordinates. BTF is typically obtained by measurement of thousands of images covering many combinations of illumination and viewing angles. However, the large size of such measurements has prohibited their practical exploitation in any sensible application until recently. During the last few years, the first BTF measurement, compression, modeling, and rendering methods have emerged. In this paper, we categorize, critically survey, and psychophysically compare such approaches, which were published in this newly arising and important computer vision and graphics area.

A psychophysically validated metric for bidirectional texture data reduction

Bidirectional Texture Functions (BTF) are commonly thought to provide the most realistic perceptual experience of materials from rendered images. The key to providing efficient compression of BTFs is the decision as to how much of the data should be preserved. We use psychophysical experiments to show that this decision depends critically upon the material concerned. Furthermore, we develop a BTF derived metric that enables us to automatically set a materials compression parameters in such a way as to provide users with a predefined perceptual quality. We investigate the correlation of three different BTF metrics with psychophysically derived data. Eight materials were presented to eleven naive observers who were asked to judge the perceived quality of BTF renderings as the amount of preserved data was varied. The metric showing the highest correlation with the thresholds set by the observers was the mean variance of individual BTF images. This metric was then used to automatically determine the material-specific compression parameters used in a vector quantisation scheme. The results were successfully validated in an experiment with six additional materials and eighteen observers. We show that using the psychophysically reduced BTF data significantly improves performance of a PCA-based compression method. On average, we were able to increase the compression ratios, and decrease processing times, by a factor of four without any differences being perceived.

A Fast Probabilistic Bidirectional Texture Function Model

The bidirectional texture function (BTF) describes rough texture appearance variations due to varying illumination and viewing conditions. Such a function consists of thousands of measurements (images) per sample. Resulted BTF size excludes its direct rendering in graphical applications and some compression of these huge BTF data spaces is obviously inevitable. In this paper we present a novel fast probabilistic model-based algorithm for realistic BTF modelling allowing such an efficient compression with possibility of direct implementation inside the graphics card. The analytical step of the algorithm starts with the BTF space segmentation and range map estimation of the BTF surface followed by the spectral and spatial factorisation of selected sub-space multispectral texture images. Single monospectral band-limited factors are independently modelled by their dedicated causal autoregressive models (CAR). During rendering the corresponding sub-space images of arbitrary size are synthesised and both multispectral and range information is combined in a bump mapping filter of the rendering hardware according to view and illumination positions. The presented model offers huge BTF compression ratio unattainable by any alternative sampling-based BTF synthesis method. Simultaneously this model can be used to reconstruct missing parts of the BTF measurement space.

On uniform resampling and gaze analysis of bidirectional texture functions

The use of illumination and view-dependent texture information is recently the best way to capture the appearance of real-world materials accurately. One example is the Bidirectional Texture Function. The main disadvantage of these data is their massive size. In this article, we employ perceptually-based methods to allow more efficient handling of these data. In the first step, we analyse different uniform resampling by means of a psychophysical study with 11 subjects, comparing original data with rendering of a uniformly resampled version over the hemisphere of illumination and view-dependent textural measurements. We have found that down-sampling in view and illumination azimuthal angles is less apparent than in elevation angles and that illumination directions can be down-sampled more than view directions without loss of visual accuracy. In the second step, we analyzed subjects gaze fixation during the experiment. The gaze analysis confirmed results from the experiment and revealed that subjects were fixating at locations aligned with direction of main gradient in rendered stimuli. As this gradient was mostly aligned with illumination gradient, we conclude that subjects were observing materials mainly in direction of illumination gradient. Our results provide interesting insights in human perception of real materials and show promising consequences for development of more efficient compression and rendering algorithms using these kind of massive data.

On optimal resampling of view and illumination dependent textures

The use of illumination and view dependent textural information is one way to capture the realistic appearance of genuine materials. One example of such data is the bidirectional texture function. The main disadvantage of these data, that makes their further application very difficult, is their massive size. Perceptually-based methods can determine optimal uniform resampling of these data that allows considerable reduction of a number of view and illumination dependent samples. In this paper we propose to achieve this goal by means of a psychophysical study, comparing original data rendering with rendering of their uniformly resampled version over the hemisphere of illumination and view dependent textural measurements. The resampling was done separately for elevation and azimuthal angles as well as in illumination and view space. Our results shown promising consequences for compression and modeling algorithms using this kind of massive data.

Analyzing and predicting anisotropic effects of BRDFs

The majority of the materials we encounter in the real-world have variable reflectance when rotated along a surface normal. This view and illumination azimuthally-variable behavior is known as visual anisotropy. Such behavior can be represented by a four-dimensional anisotropic BRDF that characterizes the anisotropic appearance of homogeneous materials. Unfortunately, most past research has been devoted to simplistic three dimensional isotropic BRDFs. In this paper, we analyze and categorize basic types of BRDF anisotropy, use a psychophysical study to assess at which conditions can isotropic appearance be used without loss of details in material appearance. To this end, we tested the human impression of material anisotropy on various shapes and under two illuminations. We conclude that subjects sensitivity to anisotropy declines with increasing complexity of 3D geometry and increasing uniformity of illumination environment. Finally, we derive and perceptually validate a computationally efficient measure of material visual anisotropy.

Spatially Varying Bidirectional Reflectance Distribution Functions

The surface texture of smooth materials, e.g., polished woods or stones, etc., has an appearance which exhibits material-specific behavior dependent on viewing and lighting conditions. To account for these appearance factors such textures can be represented by Spatially Varying BRDFs (SVBRDF). The SVBRDF representation of material can be viewed as a spatial collection of BRDFs distributed over the surface to simulate the appearance of smooth materials. As an essential part of SVBRDF representations are BRDFs, this chapter starts with description of Bidirectional Reflectance Distribution Functions (BRDFs) and their parameterization, compression, and modeling methods. Next, techniques of their spatial extension to SVBRDF modeling and editing are described.

A psychophysical evaluation of texture degradation descriptors

Delivering digitally a realistic appearance of materials is one of the most difficult tasks of computer vision. Accurate representation of surface texture can be obtained by means of view- and illuminationdependent textures. However, this kind of appearance representation produces massive datasets so their compression is inevitable. For optimal visual performance of compression methods, their parameters should be tuned to a specific material. We propose a set of statistical descriptors motivated by textural features, and psychophysically evaluate their performance on three subtle artificial degradations of textures appearance. We tested five types of descriptors on five different textures and combination of thirteen surface shapes and two illuminations. We found that descriptors based on a two-dimensional causal auto-regressive model, have the highest correlation with the psychophysical results, and so can be used for automatic detection of subtle changes in rendered textured surfaces in accordance with human vision.

Bidirectional Texture Functions

The Bidirectional Texture Function is the best recent visual texture representation which can still be simultaneously measured and modeled using state-of-the-art measurement devices and computers as well as the most advanced mathematical models of visual data. Thus it is the most important representation for the high-end and physically correct surface materials appearance modeling. This chapter surveys compression and modeling approaches available for this sophisticated textural representation.

Hypogene Features in Sandstones: An Example from Carboniferous Basins of Central and Western Bohemia, Czech Republic

Concave and cavernous forms including rising wall channels, rising sets of coalesced copula, ceiling half-tube channels, separate ceiling copula, ceiling chimneys, and half-spherical upward-convex arches locally occur in surface outcrops of Carboniferous arkose sandstones in central and western Bohemia. Many of these negative forms conventionally described as tafoni and/or honeycombs have been traditionally interpreted as products of various exogenous weathering processes. Based on the line of indirect evidence, we propose an alternative interpretation in which these features represent transitional and outlet members of the morphologic suite of rising flow (MSRF), indicative of their subsurface hypogene origin. The negative forms are commonly associated with bedding planes and subvertical fractures mineralized with goethite and jarosite. The reflectance of coal particles embedded in sandstone along mineralized bedding planes (0.91–1.03% R r ) is appreciably higher with respect to those of adjacent unaltered arkose host rocks (0.61–0.85% R r ), pointing to the thermal overprint by hot fluids. Moreover, the walls of many cavities are covered by sandy-disintegrated alterite locally mineralized with gypsum, dickite, goethite, authigenic quartz, pickeringite, and bischofite. We suggest that these phenomena, including the origin of characteristic concave forms and mineralogical alterations of arkose host rocks, may have been due to warm, CO2-saturated and possibly H2S-rich brines that ascended from the deepest stratigraphic units of the Carboniferous succession via the network of subvertical tectonic fractures and migrated laterally outward along permeable bedding planes. As indicated by the apatite fission track analysis and wider geological observations, the alteration of arkose sandstones probably occurred at relatively shallow depth of burial, during the Tertiary uplift of the Bohemian Massif 15–20 Ma ago. In this environment, the alteration may have been accelerated by the effects of mixing corrosion where heated deep basinal fluids interacted with shallower interstratal waters. When the uplifted sandstone sequences eventually reached the surface, the hypogene cavities and altered cliff walls were subjected to subaerial weathering and fluvial erosion processes the effects of which were superimposed on older hypogene features.