Paper
24 July 2000 Analysis and modeling of fixation point selection for visual search in cluttered backgrounds
Author Affiliations +
Abstract
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 out 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.
© (2000) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Magnus Snorrason, James Hoffman, and Harald Ruda "Analysis and modeling of fixation point selection for visual search in cluttered backgrounds", Proc. SPIE 4029, Targets and Backgrounds VI: Characterization, Visualization, and the Detection Process, (24 July 2000); https://doi.org/10.1117/12.392532
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KEYWORDS
Target detection

Visualization

Eye models

Data modeling

Cognitive modeling

Image processing

Visual process modeling

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