On uniform resampling and gaze analysis of bidirectional texture functions

Abstract

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 paper 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 eleven 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 analysed subjects gaze fixation during the experiment. The gaze analysis confirmed resuls 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.

Effects of Approximate Filtering on the Appearance of Bidirectional Texture Functions

“…For the second and third parts of this first experiment, no significant differences were found between light directions l (F = 1.34, p > 0. 25), nor between different kernels (F = 1.32, p > 0.26). A significant interaction effect between l and d was found (F = 2.03, p < 0.05), but the post-hoc test showed no significant differences between pairs.…”

“…A perception-based metric for single-level BTFs was derived in [24], in order to achieve higher compression rates. Filip et al [3], [25] ran psychophysical tests to discard perceptually unimportant data in the BTF. Although closer to our approach, our work differs in several ways: First, we do not aim at reducing the input dataset of 2D texture images that define the BTF; instead, we focus on efficient strategies to sample such multidimensional data, and on studying the effect of pre-filtering BTFs in their perceived appearance.…”

Tri-Chrominance Texture Pattern: A New Feature Descriptor

“…In these works, the authors used functional Magnetic Resonance Imaging (fMRI) to explore the perception of color and shape. Filip et al [9] exploited gaze tracking device to identify salient areas on textured surfaces. The texture of an image can also be represented by the proper distribution of local intensity gradients.…”

Gaze-Motivated Compression of Illumination and View Dependent Textures

“…They were based on clustering, linear decomposition methods, pixel-wise reflectance models or on Markov random fields models. In recent years researchers have started to investigate human perception of BTF data and proposed methods using standard [3] or experimentally derived [4], [5] rules for enhancement of data compression while still maintaining rapid access to the data. We build on this research and exploit gaze data analysis to provide a better understanding of a way humans perceive different real-world materials, and consequently apply this knowledge for improvement of BTF data compression.…”