The Design of High-Level Features for Photo Quality Assessment
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Photo and Video Quality Evaluation: Focusing on the Subject
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part III
Photo assessment based on computational visual attention model
MM '09 Proceedings of the 17th ACM international conference on Multimedia
Sensation-based photo cropping
MM '09 Proceedings of the 17th ACM international conference on Multimedia
Personalized photograph ranking and selection system
Proceedings of the international conference on Multimedia
A framework for photo-quality assessment and enhancement based on visual aesthetics
Proceedings of the international conference on Multimedia
Proceedings of the international conference on Multimedia
Studying aesthetics in photographic images using a computational approach
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part III
Photo search by face positions and facial attributes on touch devices
MM '11 Proceedings of the 19th ACM international conference on Multimedia
Proceedings of the 20th ACM international conference on Multimedia
Intelligent photographing interface with on-device aesthetic quality assessment
ACCV'12 Proceedings of the 11th international conference on Computer Vision - Volume 2
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In this paper, an aesthetic modeling method for scenic photographs is proposed. A bottom-up approach is developed to construct an aesthetic library with bag-of-aesthetics preserving features instead of top-down methods that implement the heuristic guidelines (rule-specific features) listed in the photography literature, which is employed in previous works. The proposed method can cover both implicit and explicit aesthetic features with a learning process. The experimental results show that the proposed features in the library (92.06% in accuracy) outperform the state-of-the-art rule-specific features (83.63% in accuracy) significantly in the aesthetic quality assessment for scenic photos, and the rule-specific features are also proved to be encompassed by the proposed features. Meanwhile, it is observed from experiments that the features extracted for contrast information are more effective than those for absolute information, which is consistent with the properties of human visual systems.