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.
People are photographed thousands of times over their lifetimes. Taken together, the photos of each person form his or her visual record. Such a visual record, which we call a photobio, samples the appearance space of that individual over time, capturing variations in facial expression, pose, hairstyle, and so forth. While acquiring photobios used to be a tedious process, the advent of photo sharing tools like Facebook coupled with face recognition technology and image search is making it easier to amass huge numbers of photos of friends, family, and celebrities. As this trend increases, we will have access to increasingly complete photobios. The large volume of such collections, however, makes them very difficult to manage, and better tools are needed for browsing, exploring, and rendering them.