Welcome to the new version of CaltechAUTHORS. Login is currently restricted to library staff. If you notice any issues, please email coda@library.caltech.edu
Published November 20, 2008 | Published
Journal Article Open

Objects predict fixations better than early saliency

Abstract

Humans move their eyes while looking at scenes and pictures. Eye movements correlate with shifts in attention and are thought to be a consequence of optimal resource allocation for high-level tasks such as visual recognition. Models of attention, such as "saliency maps," are often built on the assumption that "early" features (color, contrast, orientation, motion, and so forth) drive attention directly. We explore an alternative hypothesis: Observers attend to "interesting" objects. To test this hypothesis, we measure the eye position of human observers while they inspect photographs of common natural scenes. Our observers perform different tasks: artistic evaluation, analysis of content, and search. Immediately after each presentation, our observers are asked to name objects they saw. Weighted with recall frequency, these objects predict fixations in individual images better than early saliency, irrespective of task. Also, saliency combined with object positions predicts which objects are frequently named. This suggests that early saliency has only an indirect effect on attention, acting through recognized objects. Consequently, rather than treating attention as mere preprocessing step for object recognition, models of both need to be integrated.

Additional Information

© 2008 ARVO. Received January 15, 2008; published November 20, 2008. This material is based upon work supported under a National Science Foundation Graduate Research Fellowship, National Institute of Mental Health grant T32MH019138, Office of Naval Research grant N00014-06-1-0734, National Institutes of Health grant R01 DA022777, and Swiss National Science Foundation fellowship PA00A-111447.

Attached Files

Published - EINjov08b.pdf

Files

EINjov08b.pdf
Files (3.0 MB)
Name Size Download all
md5:a189fafbf69eb778a4a47e053a23c466
3.0 MB Preview Download

Additional details

Created:
August 22, 2023
Modified:
October 17, 2023