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Author Kemelmacher-Shlizerman, Ira ♦ Seitz, Steven M. ♦ Garg, Rahul ♦ Shechtman, Eli
Source ACM Digital Library
Content type Text
Publisher Association for Computing Machinery (ACM)
File Format PDF
Language English
Abstract We present an approach for generating face animations from large image collections of the same person. Such collections, which we call photobios, are remarkable in that they summarize a person's life in photos; the photos sample the appearance of a person over changes in age, pose, facial expression, hairstyle, and other variations. Yet, browsing and exploring photobios is infeasible due to their large volume. By optimizing the quantity and order in which photos are displayed and cross dissolving between them, we can render smooth transitions between face pose (e.g., from frowning to smiling), and create moving portraits from collections of still photos. Used in this context, the cross dissolve produces a very strong motion effect; a key contribution of the paper is to explain this effect and analyze its operating range. We demonstrate results on a variety of datasets including time-lapse photography, personal photo collections, and images of celebrities downloaded from the Internet. Our approach is completely automatic and has been widely deployed as the "Face Movies" feature in Google's Picasa.
Description Affiliation: Google Inc. (Garg, Rahul) || University of Washington and Google Inc. (Seitz, Steven M.) || Adobe Inc. (Shechtman, Eli) || University of Washington (Kemelmacher-Shlizerman, Ira)
Age Range 18 to 22 years ♦ above 22 year
Educational Use Research
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2005-08-01
Publisher Place New York
Journal Communications of the ACM (CACM)
Volume Number 57
Issue Number 9
Page Count 7
Starting Page 93
Ending Page 99


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Source: ACM Digital Library