Automatic Cinemagraph Portraits

Abstract

Cinemagraphs are a popular new type of visual media that lie in-between photos and video; some parts of the frame are animated and loop seamlessly, while other parts of the frame remain completely still. Cinemagraphs are especially effective for portraits because they capture the nuances of our dynamic facial expressions. We present a completely automatic algorithm for generating portrait cinemagraphs from a short video captured with a hand-held camera. Our algorithm uses a combination of face tracking and point tracking to segment face motions into two classes: gross, large-scale motions that should be removed from the video, and dynamic facial expressions that should be preserved. This segmentation informs a spatially-varying warp that removes the large-scale motion, and a graph-cut segmentation of the frame into dynamic and still regions that preserves the finer-scale facial expression motions. We demonstrate the success of our method with a variety of results and a comparison to previous work.