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Title: Uncertainty Estimation of Visual Attention Models using Spatiotemporal Analysis
Committee:
Dr. AlRegib, Advisor
Dr. Juang, Chair
Dr. Anderson
Abstract:
The objective of the proposed research is two folds (i) analyze uncertainty in computational video saliency and (ii) design an effective uncertainty estimation algorithm tailored for video saliency detection. More specifically, we analyze eye tracking data and video content to discover general patterns of human visual attention that can be used for uncertainty estimation including: map consistency, motion, and high-level saliency feature. Based on such analysis, we design an uncertainty estimation algorithm and show its effectiveness in the application of video saliency detection.
