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Moving portraits

Published:01 September 2014Publication History
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Abstract

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.

References

  1. Ahonen, T., Hadid, A., Pietikäinen, M. Face description with local binary patterns: Application to face recognition. IEEE Trans. Pattern Anal. Mach. Intell. 28, 12 (2006), 2037--2041. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Arikan, O., Forsyth, D.A. Interactive motion generation from examples. ACM Trans. Graph. 21, 3 (2002), 483--490. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Beier, T., Neely, S. Feature-based image metamorphosis. ACM Trans. Graph. (SIGGRAPH) (1992), 35--42. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. Berg, T.L., Berg, A.C., Edwards, J., Maire, M., White, R., Teh, Y.W., Learned-Miller, E., Forsyth, D.A. Names and faces in the news. In CVPR (2004), 848--854. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. Bourdev, L., Brandt, J. Robust object detection via soft cascade. In CVPR (2005). Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Bregler, C., Covell, M., Slaney, M. Video rewrite: Driving visual speech with audio. ACM Trans. Graph. (SIGGRAPH) (1997), 75--84. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. Chen, S.E., Williams, L. View interpolation for image synthesis. ACM Trans. Graph. (SIGGRAPH) (1993), 279--288. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Dalal, N., Triggs, B. Histograms of oriented gradients for human detection. In CVPR (2005), 886--893. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Everingham, M., Sivic, J., Zisserman, A. "Hello! My name is … Buffy"---Automatic naming of characters in TV video. In Proceedings of the British Machine Vision Conference (2006).Google ScholarGoogle ScholarCross RefCross Ref
  10. Goldman, D.B., Gonterman, C., Curless, B., Salesin, D., Seitz, S.M. Video object annotation, navigation, and composition. In UIST (2008), 3--12. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Huang, G.B., Ramesh, M., Berg, T., Learned-Miller, E. Labeled faces in the wild: A database for studying face recognition in unconstrained environments. Technical Report 07-49. University of Massachusetts, Amherst, 2007.Google ScholarGoogle Scholar
  12. Joshi, N., Szeliski, R., Kriegman, D.J. PSF estimation using sharp edge prediction. In CVPR (2008).Google ScholarGoogle Scholar
  13. Katz, S., Tal, A., Basri, R. Direct visibility of point sets. ACM Trans. Graph. (SIGGRAPH 2007) 26, 3 (2007). Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. Kemelmacher-Shlizerman, I., Sankar, A., Shechtman, E., Seitz, S.M. Being John Malkovich. In ECCV (2010). Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. Kemelmacher-Shlizerman, I., Shechtman, E., Garg, R., Seitz, S.M. Exploring photobios. ACM Trans. Graph. 30, 4 (2011), 61:1--61:10. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. Kovar, L., Gleicher, M., Pighin, F. Motion graphs. ACM Trans. Graph. (SIGGRAPH) (2002), 473--482. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. Lasseter, J. Principles of traditional animation applied to 3D computer animation. ACM Trans. Graph. (SIGGRAPH) (1987), 35--44. Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. Levoy, M., Hanrahan, P. Light field rendering. ACM Trans. Graph. (SIGGRAPH) (1996), 31--42. Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. Marr, D., Hildreth, E. Theory of edge detection. Proc. R. Soc. Lond. B 207 (1980), 187--217.Google ScholarGoogle ScholarCross RefCross Ref
  20. Nalwa, V.S., Binford, T.O. On detecting edges. IEEE Trans. Pattern Anal. Mach. Intell. 8, (1986), 699--714. Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. Picasa, 2010. http://googlephotos.blogspot.com/2010/08/picasa-38-face-movies-picnik.html.Google ScholarGoogle Scholar
  22. Seitz, S.M., Dyer, C.R. View morphing. ACM Trans. Graph. (SIGGRAPH) (1996), 21--30. Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. Shashua, A. Geometry and photometry in 3D visual recognition. PhD thesis, Massachusetts Institute of Technology, Cambridge, MA (1992). Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. Szeliski, R., Shum, H.Y. Creating full view panoramic image mosaics and environment maps. ACM Trans. Graph. (SIGGRAPH) (1997), 251--258. Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. Zhang, L., Snavely, N., Curless, B., Seitz, S.M. Spacetime faces: High resolution capture for modeling and animation. ACM Trans. Graph. (SIGGRAPH) (2004), 548--558. Google ScholarGoogle ScholarDigital LibraryDigital Library

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      • Published in

        cover image Communications of the ACM
        Communications of the ACM  Volume 57, Issue 9
        September 2014
        94 pages
        ISSN:0001-0782
        EISSN:1557-7317
        DOI:10.1145/2663191
        • Editor:
        • Moshe Y. Vardi
        Issue’s Table of Contents

        Copyright © 2014 ACM

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        Publication History

        • Published: 1 September 2014

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