Eye Tracking Based Saliency for Automatic Content Aware Image Processing

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. Tracking the photographer’s eyes allows a direct, passive means to estimate scene saliency. We show that saliency estimation is sometimes an ill-posed posed problem for automatic algorithms, made wellposed by the availability of recorded eye tracks. We instrument several content-aware image processing algorithms with eye track based saliency estimation, producing photos that accentuate the parts of the image originally viewed.