A Subjective Evaluation of Texture Synthesis Methods

Abstract

This paper presents the results of a user study which quantifies the relative and absolute quality of example-based texture synthesis algorithms. In order to allow such evaluation, a list of texture properties is compiled, and a minimal representative set of textures is selected to cover these. Six texture synthesis methods are compared against each other and a reference on a selection of twelve textures by non-expert participants (N = 67). Results demonstrate certain algorithms successfully solve the problem of texture synthesis for certain textures, but there are no satisfactory results for other types of texture properties. The presented textures and results make it possible for future work to be subjectively compared, thus facilitating the development of future texture synthesis methods.

Evaluating Realism in Example-based Terrain Synthesis

“…Our second experiment collected data on what participants were using to judge 'realism', which we provide in our supplementary material. Kolář et al [29] undertake a subjective evaluation of texture synthesis methods. They point to a small number of previous comparative studies on tone mapping, image retargeting, and deblurring.…”

“…We chose to use a method where, for a given set of images, every possible pair of images was compared against each other, with the participant required to select which they thought was 'most realistic' (i.e., which they found most believable). We chose to use pair-wise comparison rather than the user ranking multiple methods at once (as used by Kolář et al [29]), as the former provides better consistency and better use of display space. We chose to include the real world example as one of the test cases (in Sets 1ś5) to ascertain whether any synthetic terrain performed better than real world (as occurred in the experiment run by Gain et al [21]); this is in contrast to the approach taken by Vanhoey et al [57] in which they compared all stimuli against a reference.…”

Realism in Data-Based Terrain Synthesis

“…Texture-optimization algorithms perform comparably well to other example-based texture synthesis methods as evidenced from a subjective evaluation of texture synthesis methods by Kolář et al [83]. It follows that if other texture synthesis methods are worth investigating for adaptation to terrain synthesis, then texture-optimization is worth exploring as well.…”

“…However, little research has been done on them in recent years due to them being outperformed in both quality and speed by the state-of-the-art pixel-based and texture-optimization methods. In addition, a subjective study of texture synthesis methods by Kolář et al [83] rated the texture-optimization method by Kaspar et al [80] to have the best overall quality for synthesizing a wide range of textures.…”

Identificação de Características e Propriedades Morfológicas em Texturas Táteis: Estudo sobre Gráficos Educativos e Cartografias para Crianças com Deficiência Visual

“…A textura tem sido uma variável fundamental no desenvolvimento de material gráfico para fins educacionais para pessoas com cegueira (Heller, 1989;Holmes et al, 1998). No entanto, suas características táteis não foram investigadas, como tem sido feito em relação às texturas visuais (Elkharraz et al, 2014;Kolar et al, 2017;López et al, 2008), ou mais especificamente, as propriedades comunicativas das texturas táteis a serem aplicadas no design de produtos (Karlsson & Velasco, 2007;Picard et al, 2003), bem como medidas de rugosidade/ Rev. Bras.…”