08 Nov Colour Group GB 2023 Awards Meeting
2023 Colour Group (GB) Awards Meeting to honour this year’s recipients of the WD Wright Post-Graduate Student and Robert WG Hunt Poster Awards.
2 pm – Opening remarks
2:10 pm – Introduction to awards
WD Wright Awards
2:15 pm – Maria Federica Norelli, Northeastern University London
The use of colour names over repeated trials
2:30 pm – Benjamin Evans, City, University of London
The colour vision screener: A multi-centre study
2:45 pm – Joyce Dixon, University of Edinburgh
‘Mr Syme’s useful little work’: Colour, collecting and zoological image-making, 1820-1850
3 pm – Halstead-Granville Tea
3:40 pm – Ilgin Cebioglu, Lemona Zhang, and Hamed Karimipour
ICVS Summer School presentation
Robert WG Hunt Awards
4 pm – Ruili He, University of Leeds
Accurate colour reproduction of human face using 3D printing technology
4:15 pm – Yan Lu, University of Leeds
Comparison of regression techniques to predict attractiveness from facial colour cues
4:30 pm – Award presentations and photos
4:40 pm – Upcoming events
4:45 pm – Closing remarks
Speaker Abstracts
Maria Federica Norelli, Northeastern University London
The use of colour names over repeated trials
This study investigates the effects of the duration of the experimental task on the use of colour names. In a lab-based colour naming experiment, we asked 17 English speakers to give unconstrained verbal responses to a series of 216 colour stimuli, presented randomly one at a time against 7 different backgrounds. We collected a total number of 26,504 unconstrained colour name responses. Firstly, we consider the global entropy of the distribution of responses as a measure of all participants’ colour vocabulary richness (Shannon, 1948). We used the order of appearance of the backgrounds to group the responses in 7 bins and measured the entropy of colour naming responses for each bin. Our results show that the richness of colour vocabulary decreases as a function of the task duration, with a maximum of 4.3 bits for the first bin and a minimum entropy of 3.8 bits for the latter bin. Secondly, we examined which colour names became more popular over time as the vocabulary became impoverished. We found a positive correlation (R2 = 0.8) between the use of BCTs and time-on-task, and a negative correlation in the case of non-BCTs (R2 = -0.5), supporting that BCTs are easier to name than non-BCTs. However, participants used significantly more often secondary basics (n = 5: brown, orange, grey, purple, and pink) (M = 1039, SD = 67) than primary basics (n = 6: black, blue, green, red, yellow, and white) (M = 773, SD = 49) over the 7 ordered backgrounds, t(12) = -8.48, p < .001, suggesting that secondary basics overall may cover larger regions of the cone excitation space than primary basics. Consistent with this explanation, a Pearson analysis showed a strong correlation (R2 = 0.6) between frequency of BTCs and their corresponding volume in LMS cone excitation space.
Benjamin Evans, City, University of London
The colour vision screener: A multi-centre study
The use of colour coding in transport and other visually demanding working environments has increased significantly in recent years and it has become more important to be able to screen efficiently for colour vision deficiency. The Colour Vision Screener (CVS) test was developed to address the issues present in conventional methods of colour vision screening which often fail to pass all normal trichromats and correctly identify those with congenital and / or acquired colour vision deficiency.
A multi-centre study was carried out to validate the CVS and establish the test-retest reliability, sensitivity, and specificity. These statistical measures were then compared to the `gold standard’ reference for screening for red/green congenital colour vision deficiency – the Ishihara pseudoisochromatic plate test. An exploratory study was also carried out to establish the efficacy of the CVS when used at home on commercially available visual displays with the sRGB colour mode.
The results indicate that only a small percentage of those with congenital colour vision deficiency are expected to pass the CVS (∼ 0.5% of deutans and < 0.1% of protans). The CVS test was found to have high test-retest reliability, sensitivity, and specificity. Critically the results of the multi-centre study demonstrate that CVS is easy to use and can achieve a high sensitivity without sacrificing specificity when carried out using calibrated visual displays.
Joyce Dixon, University of Edinburgh
‘Mr Syme’s useful little work’: Colour, collecting and zoological image-making, 1820-1850
This paper is anchored in the pages of three works of 19th-century natural history: The Zoology of the Northern Parts of British America (1829–37) by John Richardson (1787–1865); Illustrations of the Zoology of South Africa (1838–49) by Andrew Smith (1797–1872); and The Zoology of the Voyage of H.M.S. Beagle (1839–43) by Charles Darwin (1809–1882).
Each was received by its British audience as an object of aesthetic, scientific and colonial value. Each was the result of the exploratory travels of its respective author overseas. Each contains lushly-depicted and minutely-described renderings of zoological subjects. And each is indebted to Patrick Syme’s colour manual Werner’s Nomenclature of Colours (1814/1821) for its chromatic vocabulary.
This paper will explore the exact nature of the ‘usefulness’ of Syme’s book in relation to these works, including the assortment of written, visual and biological matter underpinning them. Straddling the tropics with Darwin, skirting the Arctic with Richardson and exploring the South African interior with Smith, this paper will excavate a vast and under-researched archive of diversely-coloured materials, amassed at the furthest fringes of British exploration and colonial reach.
More often stated than investigated, the multifarious utility of Werner’s Nomenclature of Colours to the 19th-century naturalist will be revealed: as an essential piece of travelling apparatus; as a device for the translation of zoological colour; and as a lexicon of standard terms, injecting its exacting colour concepts into the ephemeral inventories of expedition archives, and into the fine-tuned remediations of zoological ‘imagetexts’.
Ruili He, University of Leeds
Accurate colour reproduction of human face using 3D printing technology
The colour of the face is one of the most significant factors in appearance and perception of an individual. With the rapid development of colour 3D printing technology and 3D imaging acquisition techniques, it is possible to achieve skin colour reproduction with the application of colour management. However, due to the complicated skin structure with uneven and non-uniform surface, it is challenging to obtain accurate skin colour appearance and reproduce it faithfully using 3D colour printers. The aim of this study was to improve the colour reproduction accuracy of the human face using 3D printing technology. A workflow of 3D colour image reproduction was developed, including 3D colour image acquisition, 3D model manipulation, colour management, colour 3D printing, postprocessing and colour reproduction evaluation. Most importantly, the colour characterisation methods for the 3D imaging system and the colour 3D printer were comprehensively investigated for achieving higher accuracy.
Yan Lu, University of Leeds
Comparison of regression techniques to predict attractiveness from facial colour cues
Various facial colour cues (average/local skin colour, colour contrasts, colour variations, etc.) were identified as valid predictors of facial attractiveness. Conventional studies on single colour variables simplified the complex nature of attractiveness judgement on real human faces. However, predicting attractiveness from various colour cues is difficult due to the high number of candidate variables and their correlations. In this study, multivariate statistical techniques and machine learning (ML) algorithms were utilized to model the relationship between facial attractiveness and a large number of colour variables using Chinese samples.
One hundred images of real human faces were used as the experimental materials, with the colour rigorously controlled to represent the naturally occurring facial colour variations in Chinese populations. Two separate attractiveness evaluation data were collected through psychophysical experiments as training and testing dataset, respectively. We proposed eight strategies for robust regression of the high-dimensional dataset based on three techniques: subset selection (forward, backward stepwise), dimension reduction (principal component regression, partial least-squares regression), and regularization (Ridge, Lasso, Elastic Net regression).
Model performance was evaluated by the predictive accuracy, the goodness of fit, and the selection of colour predictors. Results showed the out-of-sample root-mean-square error for dimension reduction and regularization methods was better than the classical least-squares. The best ML algorithm predicted facial attractiveness within 0.67 points on a 7-point scale. Different predictors were selected depending on methods but several common predictors were revealed as important features including skin lightness, overall colour variation, and colour contrast around eyebrows.
Here we evaluated statistical and ML algorithms for utilizing facial colour cues for attractiveness prediction based on realistic skin models. From the perspective of both well-predicting and interpretable, ML techniques with feature selection were recommended for attractiveness modelling. Our results also demonstrated the importance of colour to facial attractiveness which is comparable to those structural features.