Wetpaint: Scraping Through Multi-Layered Images
Name
Ishii_Wetpaint Scraping.pdf
Size
1.8 MB
Format
Adobe PDF
Checksum (MD5)
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Author(s)
Bonanni, Leonardo Amerigo
Xiao, Xiao
Hockenberry, Matthew
Subramani, Praveen
Ishii, Hiroshi
Seracini, Maurizio
Schulze, Jurgen
Date Issued
April 2009
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
Abstract
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.
MIT Department
Program in Media Arts and Sciences (Massachusetts Institute of Technology)
Terms of Use
Attribution-Noncommercial-Share Alike 3.0 Unported
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1145/1518701.1518789
