Enhancing semantic features with compositional analysis for scene recognition
ECCV'12 Proceedings of the 12th international conference on Computer Vision - Volume Part III
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
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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Computational aesthetics is the study of applying machine learning techniques to identify aesthetically pleasing imagery. Prior work used online datasets scraped from large user communities like Flikr to get labeled data. However, online imagery represents results late in the media generation process, as the photographer has already framed the shot and then picked the best results to upload. Thus, this technique can only identify quality imagery once it has been taken. In contrast, automatically creating pleasing imagery requires understanding the imagery present earlier in the process. This paper applies computational aesthetics techniques to a novel dataset from earlier in that process in order to understand how the problem changes when an autonomous agent, like a robot or a real-time camera aid, creates pleasing imagery instead of simply identifying it.