I n this tutorial, we define and discuss key aspects of the problem of computational inference of aesthetics and emotion from images. We begin with a background discussion on philosophy, photography, paintings, visual arts, and psychology. This is followed by introduction of a set of key computational problems that the research community has been striving to solve and the computational framework required for solving them. We also describe data sets available for performing assessment and outline several real-world applications where research in this domain can be employed. A significant number of papers that have attempted to solve problems in aesthetics and emotion inference are surveyed in this tutorial. We also discuss future directions that researchers can pursue and make a strong case for seriously attempting to solve problems in this research domain.

The relation between perceptual image quality and naturalness was investigated by varying the colorfulness and hue of color images of natural scenes. These variations were created by digitizing the images, subsequently determining their color point distributions in the CIELUV color space and finally multiplying either the chroma value or the hue-angle of each pixel by a constant. During the chroma/hue-angle transformation the lightness and hue-angle/chroma value of each pixel were kept constant. Ten subjects rated quality and naturalness on numerical scales. The results show that both quality and naturalness deteriorate as soon as hues start to deviate from the ones in the original image. Chroma variation affected the impression of quality and naturalness to a lesser extent than did hue variation. In general, a linear relation was found between image quality and naturalness. For chroma variation, however, a small but systematic deviation could be observed. This deviation reflects the subjects' preference for more colorful but, at the same time, somewhat unnatural images.

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DOI to the publisher's website. • The final author version and the galley proof are versions of the publication after peer review. • The final published version features the final layout of the paper including the volume, issue and page numbers. Link to publication General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. • Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal. If the publication is distributed under the terms of Article 25fa of the Dutch Copyright Act, indicated by the "Taverne" license above, please follow below link for the End User Agreement:

Images elicit a variety of emotional responses related to image content, overall aesthetic appeal, or a combination of both. One aspect of aesthetic appeal is harmony: the pleasing or congruent arrangement of parts producing internal calm or tranquility. We conducted a series of experiments to identify what factors, if any, could predict harmony in an image. Subjective judgments of image harmony were collected for images representative of typical consumer photography. Our results show that for simplified images (pixelated to control for emotional responses) reasons for image harmony are fairly dependent on the viewer, but typically involve edge contrast, average lightness, range of lightness, or the inclusion of Gestalt principles. Extraction of global image features may help to explain results with black and white and color images.Index Terms-image harmony, image quality, computational assessment, consumer photography