数码人像照片美感评价研究

系统仿真学报 ›› 2016, Vol. 28 ›› Issue (10): 2298-2303.

数码人像照片美感评价研究

陶则恩, 普园媛, 徐丹, 刘屹位

云南大学信息学院,昆明 650504

收稿日期:2016-05-30 修回日期:2016-07-14 出版日期:2016-10-08 发布日期:2020-08-13
作者简介:陶则恩(1989-),男,云南宣威,硕士生,研究方向为数字图像处理、视觉艺术理解、计算美学; 普园媛(通讯作者1972-),女,云南晋宁,副教授,研究方向为非真实感绘制、视觉艺术理解、模式识别。
基金资助:
国家自然科学基金(61163019,61271361,61462093),云南省教育厅产业化项目(2016CYH03),云南大学中青年骨干教师项目(XT412003)

Aesthetic Assessment for Digital Portrait Photos

Tao Zeen, Pu Yuanyuan, Xu Dan, Liu Yiwei

School of Information Science and Engineering, Yunnan University, Kunming 650504, China

Received:2016-05-30 Revised:2016-07-14 Online:2016-10-08 Published:2020-08-13

摘要/Abstract

摘要： 计算美感评价是一个具有挑战性的研究方向,随着数码产品广泛使用,人们对数码产品的智能化需求提高,数码照片的数量呈爆炸式增长,怎样判断这些照片的好坏呢?传统的照片美感评价主要靠专家或摄影者凭借自己对美的理解进行主观判断,不仅速度慢,还带有很强的主观性。主要通过人脸、人眼检测,提取了数码人像的人脸比例、视觉平衡等特征,对数码人像照片美感进行评价,并与主观评价获取实验进行了比较分析。实验结果表明虽然计算美感评价与主观评价有些差异,但计算美感评价指标明确,具有一定的客观性。

关键词: 计算美学, 美感评价, 照片结构, 人脸检测, 人眼开度

Abstract: Computational aesthetic evaluation is a challenging research. With the widespread use of digital products, it needs to improve the intelligence of digital products. How are these photos judged good or bad? The traditional photo aesthetic quality evaluation mainly is done based on subjective judgment or experts or the photographer's understanding for beauty. It is not only slow, but also with highly subjective. The results of face detect and eye detect were used to calculate visual balance of digital portrait based on face proportion and other features for aesthetic assessment of digital portrait photo were extracted too. The computer aesthetic score were compared with the subjective evaluation. The results show that, although the computer aesthetic score are different from the subjective evaluation, the computer aesthetic assessment has clear and objective evaluation criteria.

Key words: computational aesthetics, aesthetic quality assessment, photo structure, face detection, human eye opening

中图分类号:

TP391.9

陶则恩, 普园媛, 徐丹, 刘屹位. 数码人像照片美感评价研究[J]. 系统仿真学报, 2016, 28(10): 2298-2303.

Tao Zeen, Pu Yuanyuan, Xu Dan, Liu Yiwei. Aesthetic Assessment for Digital Portrait Photos[J]. Journal of System Simulation, 2016, 28(10): 2298-2303.

参考文献 14

[1]	Shao J, Zhou Y.Photo Quality Assessment in Different Categories[J]. Journal of Computational Information Systems (S0887-4417), 2013, 9(8): 3209-3217.
[2]	Battiato S, Moltisanti M, Ravì F, et al. Aesthetic scoring of digital portraits for consumer applications [C]// IS&T/SPIE Electronic Imaging. USA: International Society for Optics and Photonics, 2013: 866008-866008-10.
[3]	Ravì F, Battiato S.A novel computational tool for aesthetic scoring of digital photography[C]// Conference on Colour in Graphics, Imaging, and Vision. USA: Society for Imaging Science and Technology, 2012, 2012(1): 349-354.
[4]	Bhattacharya S, Sukthankar R, Shah M.A framework for photo-quality assessment and enhancement based on visual aesthetics[C]// Proceedings of the international conference on Multimedia. USA: ACM, 2010: 271-280.
[5]	Li C, Gallagher A, Loui A C, et al.Aesthetic quality assessment of consumer photos with faces[C]// The 17th IEEE International Conference on Image Processing (ICIP), 2010. USA: IEEE, 2010: 3221-3224.
[6]	Huang X, Han X, Eckert C.OPARS: objective photo aesthetics ranking system[M]// Advances in Information Retrieval. Germany: Springer Berlin Heidelberg, 2013: 861-864.
[7]	Khan S S, Vogel D.Evaluating visual aesthetics in photographic portraiture[C]// Proceedings of the Eighth Annual Symposium on Computational Aesthetics in Graphics, Visualization, and Imaging. Annecy, France: Eurographics Association, 2012: 55-62.
[8]	Chu W T, Chen Y K, Chen K T.Size does matter: how image size affects aesthetic perception[C]// Proceedings of the 21st ACM international conference on Multimedia. USA: ACM, 2013: 53-62.
[9]	Redi M, Rasiwasia N, Aggarwal G, et al.The beauty of capturing faces: Rating the quality of digital portraits[C]// IEEE International Conference and Workshops on Automatic Face and Gesture Recognition. USA: IEEE, 2015:1-8.
[10]	Nilsson M, Nordberg J, Claesson I. Face detection using local SMQT features and split up snow classifier [C]// IEEE International Conference on Acoustics, Speech and Signal Processing, 2007, ICASSP 2007. USA: IEEE, 2007: II/589-II/592.
[11]	Nilsson M, Dahl M, Claesson I. The successive mean quantization transform [C]// Proceedings of IEEE International Conference on Acoustics, Speech,Signal (ICASSP '05), USA: IEEE, 2005: IV/429-IV/432.
[12]	吴冰, 陈步威, 李富贵, 等. 基于Hough 变换的人眼检测方法研究[J]. 河南理工大学学报(自然科学版), 2009, 27(5): 556-559.
[13]	Tzortzis G, Likas A.The minmax k-means clustering algorithm[J]. Pattern Recognition (S0031-3203), 2014, 47(7): 2505-2516.
[14]	Luo W, Wang X, Tang X.Content-based photo quality assessment[C]// 2011 IEEE International Conference on Computer Vision (ICCV). USA: IEEE, 2011: 2206-2213.