A Crowdsourcing Procedure for the Discovery of Non-Obvious Attributes of Social Image [article]

Mark Melenhorst
2014 arXiv   pre-print
Research on mid-level image representations has conventionally concentrated relatively obvious attributes and overlooked non-obvious attributes, i.e., characteristics that are not readily observable when images are viewed independently of their context or function. Non-obvious attributes are not necessarily easily nameable, but nonetheless they play a systematic role in people's interpretation of images. Clusters of related non-obvious attributes, called interpretation dimensions, emerge when
more » ... ople are asked to compare images, and provide important insight on aspects of social images that are considered relevant. In contrast to aesthetic or affective approaches to image analysis, non-obvious attributes are not related to the personal perspective of the viewer. Instead, they encode a conventional understanding of the world, which is tacit, rather than explicitly expressed. This paper introduces a procedure for discovering non-obvious attributes using crowdsourcing. We discuss this procedure using a concrete example of a crowdsourcing task on Amazon Mechanical Turk carried out in the domain of fashion. An analysis comparing discovered non-obvious attributes with user tags demonstrated the added value delivered by our procedure.
arXiv:1409.2668v1 fatcat:4ycj2yufnzhzfmwnzu5ogx6d2u