Automatic Cinemagraph Portraits

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.

[1]  Steven M. Drucker,et al.  Cliplets: juxtaposing still and dynamic imagery , 2012, UIST.

[2]  Ce Liu,et al.  Exploring new representations and applications for motion analysis , 2009 .

[3]  Maneesh Agrawala,et al.  Selectively de-animating video , 2012, ACM Trans. Graph..

[4]  Olga Veksler,et al.  Fast approximate energy minimization via graph cuts , 2001, Proceedings of the Seventh IEEE International Conference on Computer Vision.

[5]  Daniel P. Huttenlocher,et al.  Distance Transforms of Sampled Functions , 2012, Theory Comput..

[6]  Jan Kautz,et al.  Towards Moment Imagery: Automatic Cinemagraphs , 2011, 2011 Conference for Visual Media Production.

[7]  Michael Gleicher,et al.  Content-preserving warps for 3D video stabilization , 2009, ACM Trans. Graph..

[8]  Mei-Chen Yeh,et al.  A tool for automatic cinemagraphs , 2012, ACM Multimedia.

[9]  Simon Lucey,et al.  Deformable Model Fitting by Regularized Landmark Mean-Shift , 2010, International Journal of Computer Vision.

[10]  Neel Joshi,et al.  Automated video looping with progressive dynamism , 2013, ACM Trans. Graph..

[11]  Richard Szeliski,et al.  Video textures , 2000, SIGGRAPH.

[12]  VekslerOlga,et al.  Fast Approximate Energy Minimization via Graph Cuts , 2001 .

[13]  Robert C. Bolles,et al.  Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography , 1981, CACM.

[14]  Michael Gleicher,et al.  Content-preserving warps for 3D video stabilization , 2009, ACM Trans. Graph..

[15]  David Salesin,et al.  Interactive digital photomontage , 2004, ACM Trans. Graph..

[16]  Takeo Kanade,et al.  An Iterative Image Registration Technique with an Application to Stereo Vision , 1981, IJCAI.

[17]  Irfan A. Essa,et al.  Graphcut textures: image and video synthesis using graph cuts , 2003, ACM Trans. Graph..