Exploring Photobios
Venue
ACM Trans. on Graphics (Proc. SIGGRAPH), vol. 30(4) (2011) (to appear)
Publication Year
2011
Authors
Ira Kemelmacher-Shlizerman, Eli Shechtman, Rahul Garg, Steven Seitz
BibTeX
Abstract
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
crossdissolving 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.
