Purchase this article with an account.
Christoph Witzel, Sophie Wuerger, Anya Hurlbert; Variation of subjective white-points along the daylight axis and the colour of the dress. Journal of Vision 2016;16(12):744. doi: 10.1167/16.12.744.
Download citation file:
© 2017 Association for Research in Vision and Ophthalmology.
We review the evidence, from different data sets collected under different viewing conditions, illumination sources, and measurement protocols, for intra- and interobserver variability in generic subjective white-point settings along the daylight locus. By generic subjective white-point we mean the subjective white-point independent of the specific context. We specifically examine the evidence across all datasets for a blue bias in subjective white-points (i.e. increased variability or reduced sensitivity in the bluish direction). We compare the extent of daylight-locus variability generally and variability in the bluish direction specifically of subjective white points across these data sets (for different luminance levels and light source types). The variability in subjective white-point may correspond to subjective priors on illumination chromaticity. In turn, individual differences in assumptions about the specific illumination chromaticity on the dress (in the recent internet phenomenon) is widely thought to explain the individual differences in reported dress colours. We therefore compare the variability in generic white-point settings collated across these datasets with the variability in generic white-point settings made in the specific context of the dress (Witzel and ORegan, ECVP 2015). Our analysis suggests that (1) there is an overall blue bias in generic subjective white-point settings and (2) the variability in generic subjective white-point settings is insufficient to explain the variability in reported dress colours. Instead, the perceived colors of the dress depend on assumptions about the illumination that are specific to that particular photo of the dress.
Meeting abstract presented at VSS 2016
This PDF is available to Subscribers Only