Aesthetics and Emotions in Images: A Computational Perspective

Dhiraj Joshi (Kodak Research), Ritendra Datta (Google), Quang-Tuan Luong (,
Elena Fedorovskaya (Kodak Research), James Z. Wang (The Pennsylvania State University and National Science Foundation),
Jia Li (The Pennsylvania State University) and Jiebo Luo (Kodak Research)

In 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.

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Citation: Dhiraj Joshi, Ritendra Datta, Quang-Tuan Luong, Elena Fedorovskaya, James Z. Wang, Jia Li and Jiebo Luo, ``Aesthetics and Emotions in Images: A Computational Perspective,'' IEEE Signal Processing Magazine, vol. 28, no. 5, pp. 94-115, September 2011.

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