On Aesthetics and Emotions in Scene Images: A Computational Perspective

Dhiraj Joshi (FXPAL Research), Ritendra Datta (Google), Elena Fedorovskaya,
Xin Lu (The Pennsylvania State University), Quang-Tuan Luong (Terragalleria.com),
James Z. Wang (The Pennsylvania State University),
Jia Li (The Pennsylvania State University) and Jiebo Luo (University of Rochester)

In this chapter we discuss the problem of computational inference of aesthetics and emotions from images. We draw inspiration from diverse disciplines such as philosophy, photography, art, and psychology to define and understand the key concepts of aesthetics and emotions. We introduce the primary 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 for which research in this domain can be employed. This chapter discusses the contributions of a significant number of research articles that have attempted to solve problems in aesthetics and emotion inference in the last several years. We conclude the chapter with directions for future research.

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Citation: Dhiraj Joshi, Ritendra Datta, Elena Fedorovskaya, Xin Lu, Quang-Tuan Luong, James Z. Wang, Jia Li and Jiebo Luo, ``On Aesthetics and Emotions in Scene Images: A Computational Perspective,'' Scene Vision, K. Kveraga and M. Bar (eds.), MIT Press, November 2014.

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Last Modified: July 1, 2014
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