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- W2099179901 abstract "We present a computational model of human eye movements in an object class detection task. The model combines state-of-the-art computer vision object class detection methods (SIFT features trained using AdaBoost) with a biologically plausible model of human eye movement to produce a sequence of simulated fixations, culminating with the acquisition of a target. We validated the model by comparing its behavior to the behavior of human observers performing the identical object class detection task (looking for a teddy bear among visually complex non-target objects). We found considerable agreement between the model and human data in multiple eye movement measures, including number of fixations, cumulative probability of fixating the target, and scanpath distance." @default.
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- W2099179901 date "2005-12-05" @default.
- W2099179901 modified "2023-10-15" @default.
- W2099179901 title "A Computational Model of Eye Movements during Object Class Detection" @default.
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