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ICIP
2008
IEEE

A Bayesian approach to predicting the perceived interest of objects

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A Bayesian approach to predicting the perceived interest of objects
This paper presents an algorithm designed to compute the perceived interest of objects in images. We measured likelihood functions via a psychophysical experiment in which subjects rated the perceived visual interest of 562 objects in 150 images. These results were then used to determine the likelihood of perceived interest given various factors such as location, contrast, color, and edge-strength. These likelihood functions are used as part of a Bayesian formulation in which perceived interest is inferred based on the factors. Our results demonstrate that our algorithm can perform well in predicting perceived interest.
Srivani Pinneli, Damon M. Chandler
Added 30 May 2010
Updated 30 May 2010
Type Conference
Year 2008
Where ICIP
Authors Srivani Pinneli, Damon M. Chandler
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