“Candid portrait selection from video”
Conference:
Type(s):
Title:
- Candid portrait selection from video
Session/Category Title: Video and Capture
Presenter(s)/Author(s):
Abstract:
In this paper, we train a computer to select still frames from video that work well as candid portraits. Because of the subjective nature of this task, we conduct a human subjects study to collect ratings of video frames across multiple videos. Then, we compute a number of features and train a model to predict the average rating of a video frame. We evaluate our model with cross-validation, and show that it is better able to select quality still frames than previous techniques, such as simply omitting frames that contain blinking or motion blur, or selecting only smiles. We also evaluate our technique qualitatively on videos that were not part of our validation set, and were taken outdoors and under different lighting conditions.
References:
1. Albuquerque, G., Stich, T., and Magnor, M. 2007. Qualitative portrait classification. Proc. Vision, Modeling, and Visualization (VMV’07) (11), 243–252.Google Scholar
2. Albuquerque, G., Stich, T., Sellent, A., and Magnor, M. 2008. The good, the bad and the ugly: Attractive portraits from video sequences. In Proc. 5th European Conference on Visual Media Production (CVMP 2008).Google Scholar
3. Cartier-Bresson, H. 1952. The Decisive Moment. Simon & Schuster.Google Scholar
4. De la Torre Frade, F., Campoy, J., Ambadar, Z., and Cohn, J. F. 2007. Temporal segmentation of facial behavior. In International Conference on Computer Vision.Google Scholar
5. Ekman, P., and Friesen, W. V. 1978. The Facial Action Coding System: A Technique for the Measurement of Facial Movement. Consulting Psychologists Press, 577 College Avenue, Palo Alto, California 94306, 1978.Google Scholar
6. Essa, I., and Pentland, A. 1995. Facial expression recognition using a dynamic model and motion energy. In Proceedings of IEEE International Conference on Computer Vision (ICCV), IEEE Computer Society, Cambridge, MA, 360–367. Google ScholarDigital Library
7. Fasel, B., and Luettin, J. 1999. Automatic facial expression analysis: A survey. PATTERN RECOGNITION 36, 1, 259–275.Google ScholarCross Ref
8. Gray, D., Yu, K., Xu, W., and Gong, Y. 2010. Predicting facial beauty without landmarks. In Proceedings of the 11th European conference on Computer vision: Part VI, Springer-Verlag, Berlin, Heidelberg, ECCV’10, 434–447. Google ScholarDigital Library
9. Katz, D. 2009. Good morning, Megan Fox. Esquire (June).Google Scholar
10. Leyvand, T., Cohen-Or, D., Dror, G., and Lischinski, D. 2008. Data-driven enhancement of facial attractiveness. ACM Transactions on Graphics 27, 3 (Aug.), 38:1–38:9. Google ScholarDigital Library
11. Mase, K., and Pentland, A. 1991. Lipreading by optical flow. Systems and Computers 22, 6, 67–76.Google ScholarDigital Library
12. McCullagh, P., and Nelder, J. A. 1989. Generalized linear models, 2nd ed. London: Chapman & Hall.Google Scholar
13. Moorthy, A. K., Obrador, P., and Oliver, N. 2010. Towards Computational Models of Visual Aesthetic Appeal of Consumer Videos. In Proc. ECCV. Google ScholarDigital Library
14. Pantic, M., Member, S., and Rothkrantz, L. J. M. 2000. Automatic analysis of facial expressions: The state of the art. IEEE Transactions on Pattern Analysis and Machine Intelligence 22, 1424–1445. Google ScholarDigital Library
15. Sand, P., and Teller, S. 2006. Particle video: Long-range motion estimation using point trajectories. Computer Vision and Pattern Recognition, IEEE Computer Society Conference on 2, 2195–2202. Google ScholarDigital Library
16. Saragih, J. M., Lucey, S., and Cohn, J. 2009. Face alignment through subspace constrained mean-shifts. In International Conference of Computer Vision (ICCV).Google Scholar
17. Tibshirani, R. 1996. Regression Shrinkage and Selection Via the Lasso. Royal. Statist. Soc B 58, 1, 267–288.Google ScholarCross Ref
18. Wang, J., and Cohen, M. F. 2005. Very low frame-rate video streaming for face-to-face teleconference. In Proceedings of the Data Compression Conference, DCC ’05, 309–318. Google ScholarDigital Library
19. Whitehill, J., and Movellan, J. R. 2008. Personalized facial attractiveness prediction. In FG, 1–7.Google Scholar
20. Williams, C. K. I., and Rasmussen, C. E. 1995. Gaussian processes for regression. In Neural Information Processing Systems, 514–520.Google Scholar
21. Xu, L., and Mordohai, P. 2010. Automatic facial expression recognition using bags of motion words. In Proceedings of the British Machine Vision Conference, BMVA Press, 13.1–13.13. doi:10.5244/C.24.13.Google Scholar
22. Zhou, F., De la Torre, F., and Cohn, J. F. 2010. Unsupervised discovery of facial events. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR).Google Scholar
