Abstract | ||
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We present an approach for generating face animations from large image collections of the same person. Such collections, which we call photobios, sample the appearance of a person over changes in pose, facial expression, hairstyle, age, and other variations. By optimizing the order in which images are displayed and cross-dissolving between them, we control the motion through face space and create compelling animations (e.g., render a smooth transition from frowning to smiling). 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. The approach operates by creating a graph with faces as nodes, and similarities as edges, and solving for walks and shortest paths on this graph. The processing pipeline involves face detection, locating fiducials (eyes/nose/mouth), solving for pose, warping to frontal views, and image comparison based on Local Binary Patterns. 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 the basis for the Face Movies feature in Google's Picasa. |
Year | DOI | Venue |
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2011 | 10.1145/1964921.1964956 | ACM Trans. Graph. |
Keywords | DocType | Volume |
Exploring photobios,face detection,image comparison,facial expression,compelling animation,face animation,Face Movies feature,large image collection,Local Binary Patterns,face space,strong motion effect | Journal | 30 |
Issue | Citations | PageRank |
4 | 17 | 0.91 |
References | Authors | |
29 | 4 |
Name | Order | Citations | PageRank |
---|---|---|---|
Ira Kemelmacher-Shlizerman | 1 | 710 | 28.03 |
Eli Shechtman | 2 | 4340 | 177.94 |
Rahul Garg | 3 | 884 | 85.42 |
Steven M. Seitz | 4 | 8729 | 495.13 |