Providing accurate color information to online shopping
customers is important for their purchase decisions.
However, due to the multiple imaging processes that
product photos undergo, end-users often experience a color
mismatch between the color of the photo online and the
product received. Therefore, we use a crowdsourcing
approach to generate what we term CrowdColor, which is
the collective color reported by individuals using a mobile
color picker. CrowdColor serves as a color review
application from the customers’ perspectives in the form of
a color palette that represents the product color. We
perform controlled experiments to evaluate the accuracy of
CrowdColor and to understand how the effects of the
device and lighting conditions may influence the crowd’s
color perception and input tasks. The quantitative results
reveal that CrowdColor achieves high accuracy and is
positively rated overall. Based on experimental analyses,
we present design guidelines for crowdsourcing color
perception tasks.