Paper
17 June 2003 High-level aspects of oculomotor control during viewing of natural-task images
Roxanne L. Canosa, Jeff B. Pelz, Neil R. Mennie, Joseph Peak
Author Affiliations +
Proceedings Volume 5007, Human Vision and Electronic Imaging VIII; (2003) https://doi.org/10.1117/12.477375
Event: Electronic Imaging 2003, 2003, Santa Clara, CA, United States
Abstract
Eye movements are an external manifestation of selective attention and can play an important role in indicating which attributes of a scene carry the most pertinent information. Models that predict gaze distribution often define a local conspicuity value that relies on low-level image features to indicate the perceived salience of an image region. While such bottom-up models have some success in predicting fixation densities in simple 2D images, success with natural scenes requires an understanding of the goals of the observer, including the perceived usefulness of an object in the context of an explicit or implicit task. In the present study, observers viewed natural images while their eye movements were recorded. Eye movement patterns revealed that subjects preferentially fixated objects relevant for potential actions implied by the gist of the scene, rather than selecting targets based purely on image features. A proto-object map is constructed that is based on highly textured regions of the image that predict the location of potential objects. This map is used as a mask to inhibit the unimportant low-level features and enhance the important features to constrain the regions of potential interest. The resulting importance map correlates well to subject fixations on natural-task images.
© (2003) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Roxanne L. Canosa, Jeff B. Pelz, Neil R. Mennie, and Joseph Peak "High-level aspects of oculomotor control during viewing of natural-task images", Proc. SPIE 5007, Human Vision and Electronic Imaging VIII, (17 June 2003); https://doi.org/10.1117/12.477375
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CITATIONS
Cited by 8 scholarly publications.
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KEYWORDS
Eye

Visualization

Image processing

RGB color model

Calibration

Data modeling

Edge detection

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