In this paper, we present improvements to image selection and image layout for automatic photobook generating algorithms. These improvements are designed to help the user easily create a photo album, which matches the user preferences and strengthens the aesthetic quality of the photobook. Image content, composition, and metadata are utilized to determine the set of images being selected, and to suggest the layout of each page.
Automatically quantifying the aesthetic appeal of images is an interesting problem in computer science and image
processing. In this paper, we incorporate aesthetic properties and convert them into computable image features for
classifying photographs taken by amateur and professional photographers. In particular, color histograms, spatial edge
distribution, and repetition identification are used as features. Results of experiments on professional and amateur
photograph data sets confirm the discriminative power of these features.
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