Steven Scher, Joshua Gaunt, Bruce Bridgeman, Sriram Swaminarayan, James Davis
01/29/2015 01:50 PM
Computer Science
Photography provides tangible and visceral mementos of
important experiences. Recent research in content-aware
image processing to automatically improve photos relies
heavily on automatically identifying salient areas in images.
While automatic saliency estimation has achieved
estimable success, it will always face inherent challenges
where saliency involves semantic judgements involving relationships
between people or objects in the scene and the
unseen photographer. Tracking the photographer’s eyes allows
a direct, passive means to estimate scene saliency. We
instrument several content-aware image processing algorithms
with eye track based saliency estimation, producing
personalized photos that accentuate the parts of the image
important to one particular person.
