Abstract
Image aesthetic analysis is a new direction of computer vision, whose purpose is to simulate the visual perception and aesthetic criterion of human being to assess aesthetic value of a given image. Nowadays, due to the popularization of smart phones with built-in cameras, functions like automatic image management and aesthetic guidance in mobile devices are valuable and in great demand. In order to remedy the gap between the large amount of computation and the hardware limitation of mobile devices, an image aesthetic classification and evaluation system using cloud computing is built in this paper. The time consuming parts such as feature extraction and machine learning algorithms are deployed on the virtual machine in the cloud server, while the simple part such as user interface is left for client. In addition, to make full use of the cloud server, a parallel-processing strategy of feature extraction is put to use in the system The result shows that our approach achieves a promising accuracy and is well correlated with the subjective aesthetics evaluation of human. And the system is more efficient and easier to be used in mobile devices with the help of cloud computing.
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References
Wu, Y., Bauckhage, C., Thurau, C.: The good, the bad, and the ugly: Predicting aesthetic image labels. In: Proceedings of 2010 20th International Conference on Pattern Recognition, Istanbul, Turkey, pp. 1586–1589 (2010)
Li, C.C., Tsuhan, C.: Aesthetic visual quality assessment of paintings. IEEE Journal of Selected Topics in Signal Processing 3(2), 236–252 (2009)
Subhabrata, B., Rahul, S., Mubarak, S.: A framework for photo quality assessment and enhancement based on visual aesthetics. In: Proceedings of the ACM Multimedia 2010 International Conference, Firenze, Italy, pp. 271–280 (2010)
Amirshahi, S.A., Koch, M., Denzler, J., et al.: PHOG analysis of self-similarity in aesthetic images. In: Proceedings of SPIE - The International Society for Optical Engineering, Burlingame, US, p. 8291 (2012)
Datta, R., Wang, J.Z.: ACQUINE: Aesthetic quality inference engine real-time automatic rating of photo aesthetics. In: Proceedings of the ACM SIGMM International Conference on Multimedia Information Retrieval, New York, pp. 421–424 (2010)
Joshi, D., Datta, R., Fedorovskaya, E., et al.: Aesthetics and emotions in images: A computational perspective. IEEE Signal Processing Magazine 28(5), 94–115 (2011)
Wang, W.-N., Yi, J.-J.: Review for computational image aesthetics. Journal of Image and Graphics, 17(8), 893–901 (2012) (in Chinese)
Wong, L.K., Low, K.L.: Saliency-enhanced image aesthetics class prediction. In: Proceedings of 2009 IEEE International Conference on Image, Los Alamitos, pp. 997–1000 (2009)
Gao, Y., Jin, L., He, C.: Handwriting Character Recognition as a Service: A New Handwriting Recognition System based on Cloud Computing. In: International Conference on Document Analysis and Recognition, ICDAR 2011, pp. 885–889 (2011)
He, C., Jin, L., Zhou, G.: Handwriting recognition system based on cloud computing platform. Telecommunications Science, 84–89 (September 2010) (in Chinese)
Duan, P., Wang, W., et al.: Food Image Recognition Using Pervasive Cloud Computing. In: International Conference on Green Computing and Communications and IEEE Internet of Things and IEEE Cyber, Physical and Social Computing, Beijing, China, August 20-23, pp. 1631–1637 (2013)
Wang, W., Yi, J., Xu, X., Wang, L.: Computational Aesthetics of Image Classification and Evaluation. Accepted by Journal of Computer-Aided Design & Computer Graphics (in Chinese)
Machado, P., Cardoso, A.: Computing aesthetics. In: de Oliveira, F.M. (ed.) SBIA 1998. LNCS (LNAI), vol. 1515, pp. 219–228. Springer, Heidelberg (1998)
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Wang, W., Liu, J., Zhao, W., Li, J. (2014). A System of Image Aesthetic Classification and Evaluation Using Cloud Computing. In: Li, S., Liu, C., Wang, Y. (eds) Pattern Recognition. CCPR 2014. Communications in Computer and Information Science, vol 483. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-45646-0_19
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DOI: https://doi.org/10.1007/978-3-662-45646-0_19
Publisher Name: Springer, Berlin, Heidelberg
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