Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Evaluation campaigns and TRECVid
MIR '06 Proceedings of the 8th ACM international workshop on Multimedia information retrieval
Saliency-enhanced image aesthetics class prediction
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Affective image classification using features inspired by psychology and art theory
Proceedings of the international conference on Multimedia
Proceedings of the 1st ACM International Conference on Multimedia Retrieval
Saliency moments for image categorization
Proceedings of the 1st ACM International Conference on Multimedia Retrieval
Studying aesthetics in photographic images using a computational approach
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part III
Towards category-based aesthetic models of photographs
MMM'12 Proceedings of the 18th international conference on Advances in Multimedia Modeling
A multimedia retrieval framework based on automatic graded relevance judgments
MMM'12 Proceedings of the 18th international conference on Advances in Multimedia Modeling
High level describable attributes for predicting aesthetics and interestingness
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
Conceptualizing Birkhoff's aesthetic measure using Shannon entropy and Kolmogorov complexity
Computational Aesthetics'07 Proceedings of the Third Eurographics conference on Computational Aesthetics in Graphics, Visualization and Imaging
Where is the beauty?: retrieving appealing VideoScenes by learning Flickr-based graded judgments
Proceedings of the 20th ACM international conference on Multimedia
Enhancing semantic features with compositional analysis for scene recognition
ECCV'12 Proceedings of the 12th international conference on Computer Vision - Volume Part III
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Semantic Indexing and Computational Aesthetics are two closely related fields. For some aspects they are similar, complementary for others, and sometimes completely disjoint. Semantic Indexing is about automatically identifying content in natural images, namely recognizing objects and scenes. Computational Aesthetics provides a set of techniques to automatically assign a beauty degree to a given image. In our work, we enrich both types of visual analysis by exploring the synergy of those two fields. We investigate the role of Semantic Indexing techniques for Computational Aesthetics Frameworks, and, vice versa, the importance of Aesthetic features for Semantic Indexing prediction. We show the benefits and the limits of this synergy, and propose some improvements in this direction.