Performance of visual search tasks from various types of contour information

Liron Itan, Yitzhak Yitzhaky

    Research output: Contribution to journalArticlepeer-review

    Abstract

    A recently proposed visual aid for patients with a restricted visual field (tunnel vision) combines a see-through head-mounted display and a simultaneous minified contour view of the wide-field image of the environment. Such a widening of the effective visual field is helpful for tasks, such as visual search, mobility, and orientation. The sufficiency of image contours for performing everyday visual tasks is of major importance for this application, as well as for other applications, and for basic understanding of human vision. This research aims is to examine and compare the use of different types of automatically created contours, and contour representations, for practical everyday visual operations using commonly observed images. The visual operations include visual searching for items, such as cutlery, housewares, etc. Considering different recognition levels, identification of an object is distinguished from mere detection (when the object is not necessarily identified). Some nonconventional visualbased contour representations were developed for this purpose. Experiments were performed with normal-vision subjects by superposing contours of the wide field of the scene over a narrow field (see-through) background. From the results, it appears that about 85% success is obtained for searched object identification when the best contour versions are employed. Pilot experiments with video simulations are reported at the end of the paper.

    Original languageAmerican English
    Pages (from-to)392-402
    Number of pages11
    JournalJournal of the Optical Society of America A: Optics and Image Science, and Vision
    Volume30
    Issue number3
    DOIs
    StatePublished - 1 Jan 2013

    All Science Journal Classification (ASJC) codes

    • Electronic, Optical and Magnetic Materials
    • Atomic and Molecular Physics, and Optics
    • Computer Vision and Pattern Recognition

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