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abstract: "This paper discusses a scenario in which human computation is used to segment timestamped fashion images for mining trends based on visual features of garments (e.g., color and texture) and attributes of portrayed subjects (e.g., gender and age). State-of-the-art algorithms for body part detection and feature extraction can produce low quality results when parts of the body are occluded and when dealing with complex human poses. In such cases, these algorithms could benefit from the assistance of human agents. In order to jointly leverage the potential of crowds and image analysis algorithms, a game with a purpose (GWAP) is proposed, whereby players can help segment images for which specialized algorithms have failed, so as to improve the extraction of color and texture features of garments and their association with the features of the subject wearing them."