Active object recognition integrating attention and viewpoint control
Computer Vision and Image Understanding
A Model of Saliency-Based Visual Attention for Rapid Scene Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Evaluating image processing algorithms that predict regions of interest
Pattern Recognition Letters
Where people look when watching movies: Do all viewers look at the same place?
Computers in Biology and Medicine
A vector-based, multidimensional scanpath similarity measure
Proceedings of the 2010 Symposium on Eye-Tracking Research & Applications
Visual attention with contextual saliencies of a scene
Proceedings of the 7th International Conference on Ubiquitous Information Management and Communication
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Saliency algorithms are applied to correlate with the overt attentional shifts, corresponding to eye movements, made by observers viewing an image. In this study, we investigated if saliency maps could be used to predict which image observers were viewing given only scanpath data. The results were strong: in an experiment with 441 trials, each consisting of 2 images with scanpath data - pooled over 9 subjects - belonging to one unknown image in the set, in 304 trials (69%) the correct image was selected, a fraction significantly above chance, but much lower than the correctness rate achieved using scanpaths from individual subjects, which was 82.4%. This leads us to propose a new metric for quantifying the importance of saliency map features, based on discriminability between images, as well as a new method for comparing present saliency map efficacy metrics. This has potential application for other kinds of predictions, e.g., categories of image content, or even subject class.