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Moving Portraits

delete2014-09-01
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PRE
AI
I
Ira Kemelmacher-Shlizerman *
E
Eli Shechtman
R
Rahul Garg
S
Steven M. Seitz
DOI:10.1145/2647750delete
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摘要

摘要

En 中文
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.
Keyword:
FACES
AI总结

AI总结

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期刊

Communications of the ACM 封面图
Communications of the ACM
IF:
12.2
论文数:
1.2W
被引数:
3.7W

机构

A
adobe systems inc.
学者数:
273
论文数: 305
被引数: 0
U
University of Washington
学者数:
8.0W
论文数: 7.0W
被引数: 12.5W
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