Wetpaint Leonardo Bonanni, Xiao Xiao, Matthew Hockenberry, Praveen Subramani, Maurizio Seracini, Hiroshi Ishii

Wetpaint
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. Scraping through image layers can be faster than comparing layers through half-transparency, especially when there are more than two layers or when the layers are distinct. 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 future work and applications for geography, design, and medicine.

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