2006
DOI: 10.2352/j.imagingsci.technol.(2006)50:4(320)
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How We Look at Photographs as Indicated by Contrast Discrimination Performance Versus Contrast Preference

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Cited by 4 publications
(7 citation statements)
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“…Tinio et al [35] conducted an experiment where subjects looked at 200 photographs of each type. They demonstrated among other things, that degradations in contrast affect judgements of photographs of human-made scenes more than those of natural scenes which contradicted previous findings that the effects of image degradations are similar across various image types [36], [37]. In this case, the explanation given was that natural scenes are more robust or tolerant to contrast degradations than humanmade scenes because humans evolved in and are well adapted to natural environments [38].…”
Section: Experimental Design and Childrencontrasting
confidence: 54%
“…Tinio et al [35] conducted an experiment where subjects looked at 200 photographs of each type. They demonstrated among other things, that degradations in contrast affect judgements of photographs of human-made scenes more than those of natural scenes which contradicted previous findings that the effects of image degradations are similar across various image types [36], [37]. In this case, the explanation given was that natural scenes are more robust or tolerant to contrast degradations than humanmade scenes because humans evolved in and are well adapted to natural environments [38].…”
Section: Experimental Design and Childrencontrasting
confidence: 54%
“…Furthermore, the preference for the original versions was independent of image category or image region. Gershoni and Kobayashi's (2006) study effectively demonstrated that the photographer's choices regarding contrast corresponded highly with observer preference. Several features of their study are directly relevant to the present study and should be noted.…”
mentioning
confidence: 85%
“…Gershoni and Kobayashi (2005; Experiments 2 and 3) also focused on the effects of variations in contrast on discrimination performance with photographs. They extended their initial psychophysical investigations by incorporating aesthetic measures in a related set of studies (Gershoni & Kobayashi, 2006). Their stimuli consisted of eight grayscale photographs by Ansel Adams (three landscapes, three portraits, and two architectural).…”
mentioning
confidence: 99%
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“…Reviewing the literature on measuring aesthetic appeal in the visual domain, we found a great variety in scales and a broad range of methods, including preference ranking tasks (Axelsson, 2007), photo quality assessment by experts (Cerosaletti & Loui, 2009) or by crowdsourcing (Lebreton, Raake, & Barkowsky, 2016), liking scales (Gershoni & Kobayashi, 2006; Tinio, Leder, & Strasser, 2011), as well as rating scales for various aesthetic descriptors, including beautiful-ugly (Jacobsen, Buchta, Köhler, & Schröger, 2004), attractive-unattractive, pleasant-unpleasant, and interesting-uninteresting (Russell & George, 1990). There is also a growing body of research dealing with deep learning and convolutional neural networks (CNN) to rate aesthetics of visual stimuli (e.g., Kong, Shen, Lin, Mech, & Fowlkes, 2016) and to model aesthetic perception (e.g., Denzler, Rodner, & Simon, 2016).…”
Section: Measuring Aesthetic Appealmentioning
confidence: 99%