Eye guidance in natural vision: reinterpreting salience

Benjamin W. Tatler, Mary M. Hayhoe, Michael F. Land, Dana H. Ballard

    Research output: Contribution to journalArticlepeer-review

    309 Citations (Scopus)

    Abstract

    Models of gaze allocation in complex scenes are derived mainly from studies of static picture viewing. The dominant framework to emerge has been image salience, where properties of the stimulus play a crucial role in guiding the eyes. However, salience-based schemes are poor at accounting for many aspects of picture viewing and can fail dramatically in the context of natural task performance. These failures have led to the development of new models of gaze allocation in scene viewing that address a number of these issues. However, models based on the picture-viewing paradigm are unlikely to generalize to a broader range of experimental contexts, because the stimulus context is limited, and the dynamic, task-driven nature of vision is not represented. We argue that there is a need to move away from this class of model and find the principles that govern gaze allocation in a broader range of settings. We outline the major limitations of salience-based selection schemes and highlight what we have learned from studies of gaze allocation in natural vision. Clear principles of selection are found across many instances of natural vision and these are not the principles that might be expected from picture-viewing studies. We discuss the emerging theoretical framework for gaze allocation on the basis of reward maximization and uncertainty reduction.

    Original languageEnglish
    Article number5
    Pages (from-to)-
    Number of pages23
    JournalJournal of Vision
    Volume11
    Issue number5
    DOIs
    Publication statusPublished - 2011

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