TY - CONF T1 - Odd Leaf Out: Improving Visual Recognition with Games T2 - Privacy, security, risk and trust (passat), 2011 ieee third international conference on and 2011 ieee third international conference on social computing (socialcom) Y1 - 2011 A1 - Hansen,D. L A1 - Jacobs, David W. A1 - Lewis,D. A1 - Biswas,A. A1 - Preece,J. A1 - Rotman,D. A1 - Stevens,E. KW - algorithm;educational KW - classification;object KW - computational KW - computing;botany;computer KW - datasets;misclassification KW - errors;scientific KW - feedback;labeled KW - game;human KW - games;computer KW - games;image KW - image KW - leaf KW - Odd KW - Out;complex KW - recognition; KW - recognition;biology KW - tags;visual KW - tasks;computer KW - tasks;textual KW - VISION AB - A growing number of projects are solving complex computational and scientific tasks by soliciting human feedback through games. Many games with a purpose focus on generating textual tags for images. In contrast, we introduce a new game, Odd Leaf Out, which provides players with an enjoyable and educational game that serves the purpose of identifying misclassification errors in a large database of labeled leaf images. The game uses a novel mechanism to solicit useful information from players' incorrect answers. A study of 165 players showed that game data can be used to identify mislabeled leaves much more quickly than would have been possible using a computer vision algorithm alone. Domain novices and experts were equally good at identifying mislabeled images, although domain experts enjoyed the game more. We discuss the successes and challenges of this new game, which can be applied to other domains with labeled image datasets. JA - Privacy, security, risk and trust (passat), 2011 ieee third international conference on and 2011 ieee third international conference on social computing (socialcom) M3 - 10.1109/PASSAT/SocialCom.2011.225 ER -