Community Photo Collections: Difference between revisions
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"With the recent rise in popularity of Internet photo sharing sites like Flickr and Google, community photo collections (CPCs) have emerged as a powerful new type of image dataset. For example, a search for “Notre Dame Paris” on Flickr yields more than 50,000 images showing the cathedral from myriad viewpoints and appearance conditions. This kind of data presents a singular opportunity: to reconstruct the world’s geometry using the largest known, most diverse, and largely untapped, multi-view stereo dataset ever assembled. What makes the dataset unusual is not only its size, but the fact tha it has been captured “in the wild”—not in the laboratory." | "With the recent rise in popularity of Internet photo sharing sites like Flickr and Google, community photo collections (CPCs) have emerged as a powerful new type of image dataset. For example, a search for “Notre Dame Paris” on Flickr yields more than 50,000 images showing the cathedral from myriad viewpoints and appearance conditions. This kind of data presents a singular opportunity: to reconstruct the world’s geometry using the largest known, most diverse, and largely untapped, multi-view stereo dataset ever assembled. What makes the dataset unusual is not only its size, but the fact tha it has been captured “in the wild”—not in the laboratory." | ||
(http://opendotdotdot.blogspot.com/2007/11/3d-digital-commons-as-metaphor.html) | (http://opendotdotdot.blogspot.com/2007/11/3d-digital-commons-as-metaphor.html) | ||
[[Category:Media]] | [[Category:Media]] | ||
Revision as of 08:27, 27 July 2010
CPC's are another name for internet photo sharing sites such as Flickr.
URL = http://grail.cs.washington.edu/projects/cpc/
Description
"With the recent rise in popularity of Internet photo sharing sites like Flickr and Google, community photo collections (CPCs) have emerged as a powerful new type of image dataset. For example, a search for “Notre Dame Paris” on Flickr yields more than 50,000 images showing the cathedral from myriad viewpoints and appearance conditions. This kind of data presents a singular opportunity: to reconstruct the world’s geometry using the largest known, most diverse, and largely untapped, multi-view stereo dataset ever assembled. What makes the dataset unusual is not only its size, but the fact tha it has been captured “in the wild”—not in the laboratory." (http://opendotdotdot.blogspot.com/2007/11/3d-digital-commons-as-metaphor.html)