  In many societies, appearing slim is considered attractive. The fashion
industry has been attempting to cater to this trend by designing outfits that
can enhance the appearance of slimness. Two anecdotal rules, widespread in the
world of fashion, are (1) choose dark clothes and (2) avoid horizontal stripes,
in order to appear slim. Thus far, empirical evidence has been unable to
conclusively determine the validity of these rules, and there is consequently
much controversy regarding the impact of both color and patterns on the visual
perception of weight. In this paper, we aim to close this gap by presenting the
results from a series of large-scale crowdsourcing studies that investigate the
above two claims. We gathered a dataset of around 1,000 images of people from
the Web together with their ground-truth weight and height, as well as clothing
attributes about colors and patterns. To elicit the effects of colors and
patterns, we asked crowd workers to estimate the weight in each image. For the
analysis, we controlled potential confounds by matching images in pairs where
the two images differ with respect to color or pattern, but are similar with
respect to other relevant aspects. We created image pairs in two ways: first,
observationally, i.e., from two real images; and second, experimentally, by
manipulating the color or pattern of clothing in a real image via photo
editing. Based on our analysis, we conclude that (1) dark clothes indeed
decrease perceived weight slightly but statistically significantly, and (2)
horizontal stripes have no discernible effect compared to solid light-colored
clothes. These results contribute to advancing the debate around the effect of
specific clothing colors and patterns and thus provide empirical grounds for
everyday fashion decisions. Moreover, our work gives an outlook on the vast
opportunities of using crowd sourcing in the modern fashion industry.
