Algorithmic Inferencing of Aesthetics and Emotion
in Natural Images: An Exposition
Ritendra Datta, Jia Li, James Z. Wang
The Pennsylvania State University
Initial studies have shown that automatic inference of
high-level image quality or aesthetics is very challenging.
The ability to do so, however, can prove beneficial in many
applications. In this paper, we define the aesthetics gap and
discuss key aspects of the problem of aesthetics and emotion
inference in natural images. We introduce precise, relevant
questions to be answered, the effect that the target audience
has on the problem specification, broad technical solution
approaches, and assessment criteria. We then report on our
effort to build real-world datasets that provide viable approaches
to test and compare algorithms for these problems,
presenting statistical analysis of and insights into them.
Full color PDF file (3.2MB)
Ritendra Datta, Jia Li and James Z. Wang, ``Algorithmic Inferencing of Aesthetics and Emotion in Natural Images: An Exposition,''
Proceedings of the IEEE
International Conference on Image Processing, pp. 105-108, San
Diego, CA, 2008.
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June 11, 2008.