Identifying fixations and saccades in eye-tracking protocols

By Dario D. Salvucci, Joseph H. Goldberg. Eye Tracking Research & Application, 2000

2,400 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Experimental and Cognitive Psychology, Human-Computer Interaction

View Paper: https://www.semanticscholar.org/paper/178dc4cd8c23f07d10ffd3797d5977c76f3dde15

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In Computer Vision and Pattern Recognition

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Citations in the corpus

Variability of eye movements when viewing dynamic natural scenes. (2010, methodology): “…labeling of fixations is not feasible on such large data sets as that of Experiment 1 ( about 40 , 000 fixations ) ; we therefore used a hybrid velocity - and dispersion - based approach ( Salvucci & Goldberg , 2000 ) and validated its parameters on a smaller data set of hand - labeled fixations .”
Towards a taxonomy of movement patterns (2008, background): “19 In a spatio-temporal sense, eye movement recordings represent a combination of constancy and repetition of fast high-speed movements between fixations.”
Eye Tracking in Human-Computer Interaction and Usability Research (2003, methodology): “Be forewarned, however, that there is no standard technique for identifying fixations (see Salvucci & Goldberg, 2000 for a good overview).”
Time-Aware Click Model (2016, background): “Xu et al. [2012] proposed a temporal hidden click model (THCM) to cope with nonsequential click actions.”
TurkerGaze: Crowdsourcing Saliency with Webcam based Eye Tracking (2015, methodology): “A standard method to extract fixations is to detect saccade onset using a velocity and/or acceleration threshold; other methods using temporal or spatial thresholds have been propsed ([30]).”
Saliency in VR: How Do People Explore Virtual Environments? (2016, methodology): “We used thresholding based on dispersion and duration of the fixations [34].”
A Random Glance at the Flight Deck: Pilots' Scanning Strategies and the Real-Time Assessment of Mental Workload (2007, background): “After all, fixations are “pauses over informative regions of interest” (Salvucci & Goldberg, 2000, p. 71).”
Predicting visual fixations on video based on low-level visual features. (2007, neutral): “This type of algorithm is generally called velocity-threshold fixation identification (Salvucci & Goldberg, 2000).”
Driver workload and eye blink duration (2011, background): “Stern et al. (1994) demonstrated that BR increases as a function of TOT.”
An adaptive algorithm for fixation, saccade, and glissade detection in eyetracking data (2010, methodology): “To demonstrate the performance of the new algorithm, it is compared against two of the most commonly used event detection algorithms: the identification by dispersion threshold (I-DT, as defined in Salvucci & Goldberg, 2000 ) and a velocity-based algorithm (commercial implementation of the algorith”
You-Do, I-Learn: Discovering Task Relevant Objects and their Modes of Interaction from Multi-User Egocentric Video (2014, methodology): “To filter saccades, we follow the velocity-based approach [31], where the average angular velocity vt over a sliding temporal window is calculated”