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Perceiving Systems Technical Report 2010

ImageFlow: Streaming Image Search

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Perceiving Systems
Varun Jampani
Jampani10 msr

Traditional grid and list representations of image search results are the dominant interaction paradigms that users face on a daily basis, yet it is unclear that such paradigms are well-suited for experiences where the user‟s task is to browse images for leisure, to discover new information or to seek particular images to represent ideas. We introduce ImageFlow, a novel image search user interface that ex-plores a different alternative to the traditional presentation of image search results. ImageFlow presents image results on a canvas where we map semantic features (e.g., rele-vance, related queries) to the canvas‟ spatial dimensions (e.g., x, y, z) in a way that allows for several levels of en-gagement – from passively viewing a stream of images, to seamlessly navigating through the semantic space and ac-tively collecting images for sharing and reuse. We have implemented our system as a fully functioning prototype, and we report on promising, preliminary usage results.

Author(s): Varun Jampani and Gonzalo Ramos and Steven Drucker
Links:
Volume: MSR-TR-2010-148
Year: 2010
Bibtex Type: Technical Report (techreport)
Address: Redmond
Electronic Archiving: grant_archive
Institution: Microsoft Research
URL: http://research.microsoft.com/apps/pubs/?id=141701

BibTex 

@techreport{jampani10_msrreport,
  title = {ImageFlow: Streaming Image Search},
  abstract = {Traditional grid and list representations of image search results are the dominant interaction paradigms that users face on a daily basis, yet it is unclear that such paradigms are well-suited for experiences where the user‟s task is to browse images for leisure, to discover new information or to seek particular images to represent ideas. We introduce ImageFlow, a novel image search user interface that ex-plores a different alternative to the traditional presentation of image search results. ImageFlow presents image results on a canvas where we map semantic features (e.g., rele-vance, related queries) to the canvas‟ spatial dimensions (e.g., x, y, z) in a way that allows for several levels of en-gagement – from passively viewing a stream of images, to seamlessly navigating through the semantic space and ac-tively collecting images for sharing and reuse. We have implemented our system as a fully functioning prototype, and we report on promising, preliminary usage results.},
  volume = {MSR-TR-2010-148},
  institution = {Microsoft Research},
  address = {Redmond},
  year = {2010},
  slug = {jampani10_msrreport},
  author = {Jampani, Varun and Ramos, Gonzalo and Drucker, Steven},
  url = {http://research.microsoft.com/apps/pubs/?id=141701}
}