Wetpaint: Scraping Through Multi-Layered Images
Author(s)
Bonanni, Leonardo Amerigo; Xiao, Xiao; Hockenberry, Matthew; Subramani, Praveen; Ishii, Hiroshi; Seracini, Maurizio; Schulze, Jurgen; ... Show more Show less
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We introduce a technique for exploring multi-layered images by scraping arbitrary areas to determine meaningful relationships. Our system, called Wetpaint, uses perceptual depth cues to help users intuitively navigate between corresponding layers of an image, allowing a rapid assessment of changes and relationships between different views of the same area. Inspired by art diagnostic techniques, this tactile method could have distinct advantages in the general domain as shown by our user study. We propose that the physical metaphor of scraping facilitates the process of determining correlations between layers of an image because it compresses the process of planning, comparison and annotation into a single gesture. We discuss applications for geography, design, and medicine.
Date issued
2009-04Department
Program in Media Arts and Sciences (Massachusetts Institute of Technology)Journal
Proceedings of the 27th international conference on Human factors in computing systems
Publisher
Association for Computing Machinery
Citation
Leonardo Bonanni, Xiao Xiao, Matthew Hockenberry, Praveen Subramani, Hiroshi Ishii, Maurizio Seracini, and Jurgen Schulze. 2009. Wetpaint: scraping through multi-layered images. In Proceedings of the 27th international conference on Human factors in computing systems (CHI '09). ACM, New York, NY, USA, 571-574.
Version: Author's final manuscript
ISBN
978-1-60558-246-7