DocumentCode :
3413018
Title :
Aesthetic composition represetation for portrait photographing recommendation
Author :
Yanhao Zhang ; Xiaoshuai Sun ; Hongxun Yao ; Lei Qin ; Qingming Huang
Author_Institution :
Sch. of Comput. Sci. & Technol., Harbin Inst. of Technol., Harbin, China
fYear :
2012
fDate :
Sept. 30 2012-Oct. 3 2012
Firstpage :
2753
Lastpage :
2756
Abstract :
In this paper, we present an intelligent portrait photographing framework for automatically recommending the suitable positions and poses in the scene of photography taken by amateurs. By analyzing aesthetic characteristics features, we propose a solution by constructing aesthetic composition representation which covers the attention composition and geometry composition to identify the underlying technique of professional photographer. First, we extract the attention composition feature of the professional photo by utilizing a visual saliency model. Then, a geometry composition feature is also presented to learn the spatial correlation. Finally, composition rules are applied to make appropriate pose and position. Experiments show our aesthetic composition representation performs well for portrait photographing recommendation.
Keywords :
feature extraction; geometry; image representation; natural scenes; recommender systems; aesthetic characteristics features; aesthetic composition representation; attention composition feature extraction; composition rules; geometry composition feature; intelligent portrait photographing recommendation; photography scene; professional photo; spatial correlation; visual saliency model; Context; Feature extraction; Geometry; Image segmentation; Photography; Quality assessment; Visualization; Aesthetic Recommendation; Attention and Geometry Composition; Composition Rules;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing (ICIP), 2012 19th IEEE International Conference on
Conference_Location :
Orlando, FL
ISSN :
1522-4880
Print_ISBN :
978-1-4673-2534-9
Electronic_ISBN :
1522-4880
Type :
conf
DOI :
10.1109/ICIP.2012.6467469
Filename :
6467469
Link To Document :
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