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.
Consumer photos are typically authored once, but need to be retargeted for reuse in various situations. These
include printing a photo on different size paper, changing the size and aspect ratio of an embedded photo to
accommodate the dynamic content layout of web pages or documents, adapting a large photo for browsing on
small displays such as mobile phone screens, and improving the aesthetic quality of a photo that was badly
composed at the capture time. In this paper, we propose a novel, effective, and comprehensive content-aware
automatic cropping (hereafter referred to as “autocrop”) method for consumer photos to achieve the above
purposes. Our autocrop method combines the state-of-the-art context-aware saliency detection algorithm, which
aims to infer the likely intent of the photographer, and the “branch-and-bound” efficient subwindow search
optimization technique, which seeks to locate the globally optimal cropping rectangle in a fast manner. Unlike
most current autocrop methods, which can only crop a photo into an arbitrary rectangle, our autocrop method
can automatically crop a photo into either a rectangle of arbitrary dimensions or a rectangle of the desired aspect
ratio specified by the user. The aggressiveness of the cropping operation may be either automatically determined
by the method or manually indicated by the user with ease. In addition, our autocrop method is extended to
support the cropping of a photo into non-rectangular shapes such as polygons of any number of sides. It may also
be potentially extended to return multiple cropping suggestions, which will enable the creation of new photos to
enrich the original photo collections. Our experimental results show that the proposed autocrop method in this
paper can generate high-quality crops for consumer photos of various types.
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