1,336 research outputs found
Gender Differences in Russian Colour Naming
In the present study we explored Russian colour naming in a web-based psycholinguistic experiment
(http://www.colournaming.com). Colour singletons representing the Munsell Color Solid (N=600 in total) were presented on a computer monitor and named using an unconstrained colour-naming method. Respondents were
Russian speakers (N=713). For gender-split equal-size samples (NF=333, NM=333) we estimated and compared (i)
location of centroids of 12 Russian basic colour terms (BCTs); (ii) the number of words in colour descriptors; (iii) occurrences of BCTs most frequent non-BCTs. We found a close correspondence between femalesâ and malesâ
BCT centroids. Among individual BCTs, the highest inter-gender agreement was for seryj âgreyâ and goluboj
âlight blueâ, while the lowest was for sinij âdark blueâ and krasnyj âredâ. Females revealed a significantly richer repertory of distinct colour descriptors, with great variety of monolexemic non-BCTs and âfancyâ colour names; in comparison, males offered relatively more BCTs or their compounds. Along with these measures, we gauged
denotata of most frequent CTs, reflected by linguistic segmentation of colour space, by employing a synthetic
observer trained by gender-specific responses. This psycholinguistic representation revealed femalesâ more
refined linguistic segmentation, compared to males, with higher linguistic density predominantly along the redgreen axis of colour space
Fast Color Space Transformations Using Minimax Approximations
Color space transformations are frequently used in image processing,
graphics, and visualization applications. In many cases, these transformations
are complex nonlinear functions, which prohibits their use in time-critical
applications. In this paper, we present a new approach called Minimax
Approximations for Color-space Transformations (MACT).We demonstrate MACT on
three commonly used color space transformations. Extensive experiments on a
large and diverse image set and comparisons with well-known multidimensional
lookup table interpolation methods show that MACT achieves an excellent balance
among four criteria: ease of implementation, memory usage, accuracy, and
computational speed
Colour appearance descriptors for image browsing and retrieval
In this paper, we focus on the development of whole-scene colour appearance descriptors for classification to be used in browsing applications. The descriptors can classify a whole-scene image into various categories of semantically-based colour appearance. Colour appearance is an important feature and has been extensively used in image-analysis, retrieval and classification. By using pre-existing global CIELAB colour histograms, firstly, we try to develop metrics for wholescene colour appearance: âcolour strengthâ, âhigh/low lightnessâ and âmulticolouredâ. Secondly we propose methods using these metrics either alone or combined to classify whole-scene images into five categories of appearance: strong, pastel, dark, pale and multicoloured. Experiments show positive results and that the global colour histogram is actually useful and can be used for whole-scene colour appearance classification. We have also conducted a small-scale human evaluation test on whole-scene colour appearance. The results show, with suitable threshold settings, the proposed methods can describe the whole-scene colour appearance of images close to human classification. The descriptors were tested on thousands of images from various scenes: paintings, natural scenes, objects, photographs and documents. The colour appearance classifications are being integrated into an image browsing system which allows them to also be used to refine browsing
Saliency-guided Adaptive Seeding for Supervoxel Segmentation
We propose a new saliency-guided method for generating supervoxels in 3D
space. Rather than using an evenly distributed spatial seeding procedure, our
method uses visual saliency to guide the process of supervoxel generation. This
results in densely distributed, small, and precise supervoxels in salient
regions which often contain objects, and larger supervoxels in less salient
regions that often correspond to background. Our approach largely improves the
quality of the resulting supervoxel segmentation in terms of boundary recall
and under-segmentation error on publicly available benchmarks.Comment: 6 pages, accepted to IROS201
Internal preference mapping of milkâfruit beverages: Influence of color and appearance on its acceptability
The individual preferences of 100 consumers between 20 and 30 years old for the color of 16 milkâfruit juice beverages (MFJB) were investigated by preference mapping technique. Consumers were asked to evaluate, just by looking at the samples, how much they liked them (from âExtremely dislikeâ to âExtremely likeâ). The color of the samples was analyzed by two different instrumental techniques. Results obtained from the instrumental color measurement showed the wide diversity in hues of the beverages available in the market, and correlations between techniques proved that both of them were appropriate to analyze color.
Results showed that participants preferred samples with orangish appearance instead of those with a whiter look. Anyway, punctuations given by the consumers suggest that generally, color of these products is not highly evaluated by consumers, as the best mean punctuation was 6.6.ConsejerĂa de InnovaciĂłn Ciencia y Empresa, Junta de AndalucĂa P11-AGR-778
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