Analysis and Modeling of Fixation Point Selection for Visual Search in Cluttered Backgrounds

M. Snorrason, H. Ruda (Charles River Analytics), and J. Hoffman (University of Delaware, Department of Psychology)

Proceedings of SPIE, Aerosense, Orlando, FL (April, 2000)

Hard-to-see targets are generally only detected by human observers once they have been fixated. Hence, understanding how the human visual system allocates fixation locations is necessary for predicting target detectability. Visual search experiments were conducted where observers searched for military vehicles in cluttered terrain. Instantaneous eye position measurements were collected using an eye tracker. The resulting data was partitioned into fixations and saccades, and analyzed for correlation with various image properties. The fixation data was used to validate our model for predicting fixation locations. This model generates a saliency map from bottom-up image features, such as local contrast. To account for top-down scene understanding effects, a separate cognitive bias map is generated. The combination of these two maps provides a fixation probability map, from which sequences of fixation points were generated.

Model-generated fixations (O) compared to eye-tracker data from human observers (*)

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