Eye movements and the control of actions in everyday life.

By M. Land. 2006

689 citations recorded by the source corpus.

The patterns of eye movement that accompany static activities such as reading have been studied since the early 1900s, but it is only since head-mounted eye trackers became available in the 1980s that it has been possible to study active tasks such as walking, driving, playing ball games and ordinary everyday activities like food preparation. This review examines the ways that vision contributes to the organization of such activities, and in particular how eye movements are used to locate the information needed by the motor system in the execution of each act. Major conclusions are that the eyes are proactive, typically seeking out the information required in the second before each act commences, although occasional 'look ahead' fixations are made to establish the locations of objects for use further into the future. Gaze often moves on before the last act is complete, indicating the presence of an information buffer. Each task has a characteristic but flexible pattern of eye movements that accompanies it, and this pattern is similar between individuals. The eyes rarely visit objects that are irrelevant to the action, and the conspicuity of objects (in terms of low-level image statistics) is much less important than their role in the task. Gaze control may involve movements of eyes, head and trunk, and these are coordinated in a way that allows for both flexibility of movement and stability of gaze. During the learning of a new activity, the eyes first provide feedback on the motor performance, but as this is perfected they provide feed-forward direction, seeking out the next object to be acted upon.

Subfields: Cognitive Neuroscience, Neurology, Human-Computer Interaction

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Citations in the corpus

Eye guidance in natural vision: Reinterpreting salience (2011, neutral): “Similarly, learner drivers fixate just ahead of the car when cornering, whereas more experienced drivers look into the bend and fixate points on the road that will be reached as much as 3 s later, thus anticipating any need for future action (Land, 2006; Land & Tatler, 2009).”
Computational visual attention systems and their cognitive foundations: A survey (2010, neutral): “[Land 2006]).”
Predicting the Future from First Person (Egocentric) Vision: A Survey (2021, background): “Indeed, gaze can serve as a clue on where a humans point their attention, so it may be an indicator for what they will do next [41].”
Vision and Driving (2010, neutral): “Land (2006) has recently provided a comprehensive overview of research on eye movements and driving, and thus here we briefly summarize some of the main findings from this research area.”
Examining the Relationship between Construction Workers’ Visual Attention and Situation Awareness under Fall and Tripping Hazard Conditions: Using Mobile Eye Tracking (2018, background): “Workers obtain feedforward information about potential sources of tripping hazards several feet ahead of them by directing their gaze downward (Land 2006; Kuzel et al. 2013; Ayres and Kelkar 2006; Buckley et al. 2011).”
What do eyes reveal about the mind?: Algorithmic inference of search targets from fixations (2015, background): “See [47] for a review of eye movements in natural vision tasks.”
You-Do, I-Learn: Discovering Task Relevant Objects and their Modes of Interaction from Multi-User Egocentric Video (2014, background): “Its anticipatory nature allows estimating which object will be used next [20, 21].”
Measuring and defining the experience of immersion in games (2008, background): “Land (2006) explains that it is during fixations that people take information in: during saccades we are effectively blind.”
Misdirection in magic: Implications for the relationship between eye gaze and attention (2008, background): “Instead, the system in general maintains the gaze very close to where the information is being extracted, thereby using the fovea’s high acuity to its full potential (see Land, 2006; Land & Furneaux, 1997; Land & Lee, 1994; Land, Mennie, & Rusted, 1999; Rayner, 1998).”
Next-active-object prediction from egocentric videos (2017, background): “[1], who propose to detect task relevant objects using a gaze tracker, exploiting the anticipatory nature of eye gaze fixation [49].”