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Photo Composition Feedback and Enhancement

Exploiting Spatial Design Categories and the Notan Dark-Light Principle

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Mobile Cloud Visual Media Computing

Abstract

In this chapter, we present techniques to provide composition feedback and enhancement for photographs. In order to suit mobile applications, we have designed systems requiring minimal input from the users. The essence of composition is to create unity in a picture, which includes the balance of visual elements from many aspects. We hereby explore several fundamental concepts in composition and develop our new methods accordingly. Albeit much exploited by artists, these concepts have barely crossed over to multimedia or computer vision research. First, we have developed a tool to categorize images by spatial design into diagonal, horizontal, vertical, and centered composition types. Composition in this regard is known to be well associated with aesthetics and emotional response. For instance, placing visual elements diagonally creates a sense of movement; and horizontal placement tends to convey tranquility. This composition analysis tool enables the retrieval of highly aesthetic exemplar images from the corpus which are similar in content and composition to the snapshot. Second, the arrangement of dark and light masses in a picture, referred to as Notan in visual art, is a crucial factor in composition. We propose an approach to adjust the tonal values in an image, targeting directly at achieving an aesthetically more appealing Notan. This method addresses composition enhancement from a high level of spatial arrangement, a remarkable difference from improving relatively low-level characteristics such as contrast and dynamic ranges.

Lei Yao done this work when she was with College of Information Sciences and Technology, The Pennsylvania State University, University Park, Pennsylvania, USA.

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Notes

  1. 1.

    http://www.digital-photography-school.com/using-diagonal-lines-in-photography.

  2. 2.

    http://www.picture-thoughts.com/photography/compos-ition/angle/.

  3. 3.

    http://www.great-landscape-photography.com/photography-composition.html.

References

  1. Abadpour, A., Kasaei, S.: Color transfer in correlated color space. Proceedings of the 2006 ACM International Conference on Virtual Reality Continuum and Its Applications, pp. 305–309. New York, USA (2006)

    Google Scholar 

  2. Adams, A.: The Print. Little Brown, Toronto (1995)

    Google Scholar 

  3. Bhattacharya, S., Sukthankar, R., Shah, M.: A coherent framework for photo-quality assessment and enhancement based on visual aesthetics. In: Proceedings of ACM Multimedia Conference, pp. 271–280 (2010)

    Google Scholar 

  4. Bouman, C.A.: Cluster: an unsupervised algorithm for modeling Gaussian mixtures (1997) http://www.ece.purdue.edu/~bouman

  5. Cohen-Or, D., Sorkine, O., Gal, R., Leyvand, T., Xu, Y.: Color harmonization. ACM Trans. Graph. 25(3), 624–630 (2006)

    Article  Google Scholar 

  6. Datta, R., Joshi, D., Li, J., Wang, J.Z.: Studying aesthetics in photographic images using a computational approach. In: Proceedings of European Conference on Computer Vision, pp. 288–301 (2006)

    Google Scholar 

  7. Datta, R., Joshi, D., Li, J., Wang, J.Z.: Image retrieval: Ideas, influences, and trends of the new age. ACM Comput. Surv. 40(2), 5:1–5:60 (2008)

    Article  Google Scholar 

  8. Feininger, A.: Principles of Composition in Photography. Thames and Hudson Ltd (1973)

    Google Scholar 

  9. Folts, J.A., Lovell, R.P., Zwahlen, F.C.: Handbook of Photography. Thompson Delmar Learning, New York (2005)

    Google Scholar 

  10. Fogarty, J., Forlizzi, J., Hudson, S.E.: Aesthetic information collages: generating decorative displays that contain information. In: Proceedings of ACM Symposium on User Interface Software and Technology, pp. 141–150 (2001)

    Google Scholar 

  11. Krages, B.P.: Photography: The Art of Composition. Allworth Press, New York (2005)

    Google Scholar 

  12. Lamb, J., Stevens, R.: Eye of the photographer. Soc. Stud. Texan 26(1), 59–63 (2010)

    Google Scholar 

  13. Lawrence, C., Zhou, J.L., Tits, A.L.: User’s guide for CFSQP version 2.0: A C code for solving (large scale) constrained nonlinear (minimax) optimization problems, generating iterates satisfying all inequality constraints. Technical Report (1994) http://drum.lib.umd.edu/handle/1903/5496

  14. Li, J.: Agglomerative connectivity constrained clustering for image segmentation. Stat. Anal. Data Min. 4(1), 84–99 (2011)

    Article  MathSciNet  Google Scholar 

  15. Li, J., Wang, J.Z., Wiederhold, G.: IRM: integrated region matching for image retrieval. In Proceedings of ACM Multimedia Conference, pp. 147–156 (2000)

    Google Scholar 

  16. Liu, L., Chen, R., Wolf, L., Cohen-Or, D.: Optimizing photo composition. Comput. Graph. Forum 29(2), 469–478 (2010)

    Article  Google Scholar 

  17. Meer, P., Georgescu, B.: Edge detection with embedded confidence. IEEE Trans. Pattern Anal. Mach. Intell. 23(12), 1351–1365 (2001)

    Article  Google Scholar 

  18. Obrador, P., Anguera, X., Oliveira, R., Oliver, N.: The role of tags and image aesthetics in social image search. In: Proceedings of the ACM SIGMM Workshop on Social Media, pp. 65–72 (2009)

    Google Scholar 

  19. Obrador, P., Oliveira, R., Oliver, N.: Supporting personal photo storytelling for social albums. In: Proceedings of ACM Multimedia Conference, pp. 561–570 (2010)

    Google Scholar 

  20. Otsu, N.: A threshold selection method from gray-level histograms. IEEE Trans. Syst. Man Cybern. 9(1), 62–66 (1979)

    Article  Google Scholar 

  21. Papadakis, N., Provenzi, E., Caselles, V.: A variational model for histogram transfer of color images. IEEE Trans. Image Process. 20, 1682–1695 (2011)

    Article  MathSciNet  Google Scholar 

  22. Paris, S., Durand, F.: A fast approximation of the bilateral filter using a signal processing approach. Int. J. Comput. Vis. 81(1), 24–52 (2009)

    Article  Google Scholar 

  23. Payne, E.: Composition of Outdoor Painting, 7th edn. Deru’s Fine Arts, x (2005)

    Google Scholar 

  24. Pitie, A.C.K.F., Dahyot, R.: Automated colour grading using colour distribution transfer. Comput. Vis. Image Underst. 107(1–2), 123–137 (2007)

    Article  Google Scholar 

  25. Pitie, F., Kokaram, A.: The linear Monge-Kantorovitch colour mapping for example-based colour transfer. In: Proceedings of the IEEE European Conference on Visual Media Production, pp. 1–9 (2007)

    Google Scholar 

  26. Pouli, T., Reinhard, E.: Progressive color transfer for images of arbitrary dynamic range. Comput. Graph. 35(1), 67–80 (2011)

    Article  Google Scholar 

  27. Raybould, B.J.: Notan painting lessons. Virtual Art Academy (2014) http://www.virtualartacademy.com/notan.html

  28. Reinhard, E., Ashikhmin, M., Gooch, B., Shirley, P.: Color transfer between images. IEEE Comput. Graph. Appl. 21(5), 34–41 (2001)

    Article  Google Scholar 

  29. Russ, J.C.: The Image Processing Handbook. CRC Press (2006)

    Google Scholar 

  30. Sorrel, C.: Nadia camera offers opinion of your terrible photos. WIRED, online, July 26 (2010)

    Google Scholar 

  31. Speed, H.: The Practice and Science of Drawing, 3rd edn. Dover Publications, New York (1972)

    Google Scholar 

  32. Sternberg, R.J.: Cognitive Psychology. Wadsworth Publishing, Florence (2008)

    Google Scholar 

  33. Tai, Y.-W., Jia, J., Tang, C.-K.: Local color transfer via probabilistic segmentation by expectation-maximization. Proc. IEEE Conf. Comput. Vis. Pattern Recognit. 1, 747–754 (2005)

    Google Scholar 

  34. Verhulst, P.F.: A note on population growth. Correspondence Mathematiques et Physiques 10, 113–121 (1838)

    Google Scholar 

  35. Wang, J.Z., Li, J., Wiederhold, G.: SIMPLIcity: semantics-sensitive integrated matching for picture libraries. IEEE Trans. Pattern Anal. Mach. Intell. 23(9), 947–963 (2001)

    Article  Google Scholar 

  36. Warren, B.: Photography: The Concise Guide. Delmar Cengage Learning, New York (2002)

    Google Scholar 

  37. Wen, C.-L., Hsieh, C.-H., Chen, B.-Y., Ouhyoung, M.: Example-based multiple local color transfer by strokes. Comput. Graph. Forum 27, 1765–1772 (2008)

    Article  Google Scholar 

  38. Werman, S.P.M., Rosenfeld, A.: A distance metric for multi-dimensional histograms. Comput. Vis. Graph. Image Process. 32, 328–336 (1985)

    Google Scholar 

  39. Xiao, X., Ma, L.: Color transfer in correlated color space. In: Proceedings of the 2006 ACM International Conference on Virtual Reality Continuum and Its Applications, pp. 305–309. New York, NY, USA (2006)

    Google Scholar 

  40. Xiao, X., Ma, L.: Gradient-preserving color transfer. Comput. Graph. Forum 28, 1879–1886 (2009)

    Article  Google Scholar 

  41. Yao, L., Suryanarayan, P., Qiao, M., Wang, J.Z., Li, J.: Oscar: on-site composition and aesthetics feedback through exemplars for photographers. Int. J. Comput. Vis. 96(3), 353–383 (2012)

    Article  Google Scholar 

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Acknowledgments

This material is based upon work supported by the National Science Foundation under Grant Nos. 0347148 and 0936948.

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Authors and Affiliations

  1. Department of Statistics, The Pennsylvania State University, University Park, PA, USA

    Jia Li

  2. Houzz Inc., Palo Alto, CA, USA

    Lei Yao

  3. College of Information Sciences and Technology, The Pennsylvania State University, University Park, PA, USA

    James Z. Wang

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  1. Jia Li
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  2. Lei Yao
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  3. James Z. Wang
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Corresponding author

Correspondence to James Z. Wang .

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Editors and Affiliations

  1. Visual Computing Group, Microsoft Research Asia, Beijing, Beijing, China

    Gang Hua

  2. Alibaba Group, Hangzhou, Zhejiang, China

    Xian-Sheng Hua

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Li, J., Yao, L., Wang, J.Z. (2015). Photo Composition Feedback and Enhancement. In: Hua, G., Hua, XS. (eds) Mobile Cloud Visual Media Computing. Springer, Cham. https://doi.org/10.1007/978-3-319-24702-1_5

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  • DOI: https://doi.org/10.1007/978-3-319-24702-1_5

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