DocumentCode
2917055
Title
Aesthetic quality classification of photographs based on color harmony
Author
Nishiyama, Masashi ; Okabe, Takahiro ; Sato, Imari ; Sato, Yoichi
Author_Institution
Inst. of Ind. Sci., Univ. of Tokyo, Tokyo, Japan
fYear
2011
fDate
20-25 June 2011
Firstpage
33
Lastpage
40
Abstract
Aesthetic quality classification plays an important role in how people organize large photo collections. In particular, color harmony is a key factor in the various aspects that determine the perceived quality of a photo, and it should be taken into account to improve the performance of automatic aesthetic quality classification. However, the existing models of color harmony take only simple color patterns into consideration-e.g., patches consisting of a few colors-and thus cannot be used to assess photos with complicated color arrangements. In this work, we tackle the challenging problem of evaluating the color harmony of photos with a particular focus on aesthetic quality classification. A key point is that a photograph can be seen as a collection of local regions with color variations that are relatively simple. This led us to develop a method for assessing the aesthetic quality of a photo based on the photo´s color harmony. We term the method `bags-of-color-patterns.´ Results of experiments on a large photo collection with user-provided aesthetic quality scores show that our aesthetic quality classification method, which explicitly takes into account the color harmony of a photo, outperforms the existing methods. Results also show that the classification performance is improved by combining our color harmony feature with blur, edges, and saliency features that reflect the aesthetics of the photos.
Keywords
feature extraction; image classification; image colour analysis; photography; aesthetic quality score; bags-of-color-patterns method; blur feature; color arrangement; color pattern; color variation; edge feature; photo color harmony; photograph aesthetic quality classification; saliency feature; Color; Computational modeling; Feature extraction; Histograms; Image color analysis; Object recognition; Visualization;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Vision and Pattern Recognition (CVPR), 2011 IEEE Conference on
Conference_Location
Providence, RI
ISSN
1063-6919
Print_ISBN
978-1-4577-0394-2
Type
conf
DOI
10.1109/CVPR.2011.5995539
Filename
5995539
Link To Document