Photo and video quality evaluation: Focusing on the subject
Inhaltsverzeichnis
Reference
Luo, Y., Tang, X.: Photo and video quality evaluation: Focusing on the subject. In: Forsyth, D., Torr, P., Zisserman, A. (eds.) ECCV 2008, Part III. LNCS, vol. 5304, pp. 386–399. Springer, Heidelberg (2008)
DOI
http://dx.doi.org/10.1007/978-3-540-88690-7_29
Abstract
Traditionally, distinguishing between high quality professional photos and low quality amateurish photos is a human task. To automatically assess the quality of a photo that is consistent with humans perception is a challenging topic in computer vision. Various differences exist between photos taken by professionals and amateurs because of the use of photography techniques. Previous methods mainly use features extracted from the entire image. In this paper, based on professional photography techniques, we first extract the subject region from a photo, and then formulate a number of high-level semantic features based on this subject and background division. We test our features on a large and diverse photo database, and compare our method with the state of the art. Our method performs significantly better with a classification rate of 93% versus 72% by the best existing method. In addition, we conduct the first study on high-level video quality assessment. Our system achieves a precision of over 95% in a reasonable recall rate for both photo and video assessments. We also show excellent application results in web image search re-ranking.
Extended Abstract
Bibtex
Used References
Wang, Z., Sheikh, H.R., Bovik, A.C.: No-reference perceptual quality assessment of JPEG compressed images. ICIP (2002)
Wang, Z., Bovik, A., Sheikh, H., Simoncelli, E.: Image quality assessment: from error visibility to structural similarity. IEEE Trans. Image Processing 13 (2004)
Sheikh, H., Bovik, A., de Veciana, G.: An information fidelity criterion for image quality assessment using natural scene statistics. IEEE Trans. Image Processing 14 (2005)
Tong, H., Li, M., Zhang, H., He, J., Zhang, C.: Classification of Digital Photos Taken by Photographers or Home Users. In: Proc. Pacific-Rim Conference on Multimedia (2004)
Datta, R., Joshi, D., Li, J., Wang, J.: Studying Aesthetics in Photographic Images Using a Computational Approach. In: Leonardis, A., Bischof, H., Pinz, A. (eds.) ECCV 2006. LNCS, vol. 3951. Springer, Heidelberg (2006)
Ke, Y., Tang, X., Jing, F.: The Design of High-Level Features for Photo Quality Assessment. In: CVPR (2006)
Freeman, M.: The Complete Guide to Light and Lighting. Ilex Press (2007)
Freeman, M.: The Photographer’s Eye: Composition and Design for Better Digital Photos. Ilex Press (2007)
London, B., Upton, J., Stone, J., Kobre, K., Brill, B.: Photography, 8th edn. Pearson Prentice Hall, London (2005)
Itten, J.: Design and Form: The Basic Course at the Bauhaus and Later. Wiley, Chichester (1975)
Manav, B.: Color-Emotion Associations and Color Preferences: A Case Study for Residences. Color Research and Application 32 (2007)
Gao, X., Xin, J., Sato, T., Hansuebsai, A., Scalzo, M., Kajiwara, K., Guan, S., Valldeperas, J., Lis, M., Billger, M.: Analysis of Cross-Cultural Color Emotion. Color Research and Application 32 (2007)
Levin, A.: Blind motion deblurring using image statistics. In: NIPS (2006)
Tokumaru, M., Muranaka, N., Imanishi, S.: Color design support system considering color harmony. In: Proc. of the 2002 IEEE International Conference on Fuzzy Systems, vol. 1 (2002)
Cohen-Or, D., Sorkine, O., Gal, R., Leyvand, T., Xu, Y.: Color harmonization. ACM Transactions on Graphics (TOG) 25 (2006)
Yan, W., Kankanhalli, M.: Detection and removal of lighting & shaking artifacts in home videos. In: Proc. of the tenth ACM international conference on Multimedia (2002)
Vapnik, V.: The Nature of Statistical Learning Theory. Springer, Heidelberg (2000)
Friedman, J., Hastie, T., Tibshirani, R.: Additive logistic regression: a statistical view of boosting (With discussion and a rejoinder by the authors). Ann. Statist 28 (2000)
Cui, J., Wen, F., Tang, X.: Real Time Google and Live Image Search Re-ranking. In: Proc. of ACM international conference on Multimedia (2008)