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Impressionist: A 3D Peekaboo Game for Crowdsourcing Shape Saliency

[+] Author Affiliations
Houpu (Hope) Yao, Max Yi Ren

Arizona State University, Tempe, AZ

Paper No. DETC2016-60081, pp. V007T06A025; 8 pages
  • ASME 2016 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
  • Volume 7: 28th International Conference on Design Theory and Methodology
  • Charlotte, North Carolina, USA, August 21–24, 2016
  • Conference Sponsors: Design Engineering Division, Computers and Information in Engineering Division
  • ISBN: 978-0-7918-5019-0
  • Copyright © 2016 by ASME


Designers often express their intents (e.g., on product functionalities and semantics) through shape features. Therefore, collecting such “salient” features from existing shapes and learning their associations with design intents will enable efficient design of new shapes. However, the acquisition of saliency knowledge from a large shape collection has not been accomplished. This paper investigates a gamification approach to this end. In addition, we propose to validate a derived saliency map by its corresponding shape recognition accuracy through crowd-sourcing. This allows a comparison across existing and the proposed saliency acquistion and computation methods. Currentl results show that the proposed method achieves statistically similar recognition accuracy to existing saliency data on a standard shape database, indicating that various saliency maps are equally valid according to the proposed saliency definition. Nonetheless, the saliency data obtained through the proposed game consistently produces reasonable viewpoints across shapes, outperforming existing curvature-based and crowdsourcing approaches. The findings from this study could lead to developments of game mechanisms that are more scalable and cost effective at saliency elicitation than existing paid crowdsourcing approaches.

Copyright © 2016 by ASME
Topics: Shapes



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