Fixation identification: The optimum threshold for a dispersion algorithm

Blignaut, Pieter

doi:10.3758/app.71.4.881

Cited by 157 publications

(148 citation statements)

References 20 publications

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“…So, as even a dispersion threshold of 2.7 would be considered a generous threshold, we decided to not go beyond this and simply set the maximum dispersion at 2.7°. Do note that we used the original Salvucci and Goldberg (2000) definition of dispersion (y max − y min + x max − x min ) which is around twice as large as most other dispersion calculations (see p. 886, Blignaut, 2009). The dispersion calculation for the humans was identical to the one implemented in the evaluated IDT algorithm.…”

Section: Methods Stimuli and Data Setmentioning

confidence: 99%

“…For example, raw data samples cluster together in a fixation, and a fixation detection algorithm should detect all samples belonging to these clusters, and reject samples outside of the clusters (see for example Fig. 2 on p. 883 in Blignaut, 2009). Unfortunately, such manual parts of an evaluation are often mentioned in passing, e.g., that Vig, Dorr, and Barth (2009, p. 399) manually tweaked their parameters until it looked good, as referenced by Mould et al (2012, p. 22).…”

Section: Evaluation Of Classification Algorithmsmentioning

confidence: 99%

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One algorithm to rule them all? An evaluation and discussion of ten eye movement event-detection algorithms

et al. 2016

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Almost all eye-movement researchers use algorithms to parse raw data and detect distinct types of eye movement events, such as fixations, saccades, and pursuit, and then base their results on these. Surprisingly, these algorithms are rarely evaluated. We evaluated the classifications of ten eyemovement event detection algorithms, on data from an SMI HiSpeed 1250 system, and compared them to manual ratings of two human experts. The evaluation focused on fixations, saccades, and post-saccadic oscillations. The evaluation used both event duration parameters, and sample-by-sample comparisons to rank the algorithms. The resulting event durations varied substantially as a function of what algorithm was used. This evaluation differed from previous evaluations by considering a relatively large set of algorithms, multiple events, and data from both static and dynamic stimuli. The main conclusion is that current detectors of only fixations and saccades work reasonably well for static stimuli, but barely better than chance for dynamic stimuli. Differing results across evaluation methods make it difficult to select one winner for fixation detection. For saccade detection, however, the algorithm by Larsson, Nyström and Stridh (IEEE Transaction on Biomedical Engineering, 60(9): [2484][2485][2486][2487][2488][2489][2490][2491][2492][2493]2013) outperforms all algorithms in data from both static and dynamic stimuli. The data also show how improperly selected algorithms applied to dynamic data misestimate fixation and saccade properties.

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Section: Methods Stimuli and Data Setmentioning

confidence: 99%

Section: Evaluation Of Classification Algorithmsmentioning

confidence: 99%

One algorithm to rule them all? An evaluation and discussion of ten eye movement event-detection algorithms

et al. 2016

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“…Fixation were identified from eye samples with the centroid-based dispersion threshold method [5]. The threshold for maximum dispersion was set to 1.67 degrees in radius, while the threshold for minimum fixation duration was set to 100 milliseconds.…”

Section: Methodsmentioning

confidence: 99%

An Eye-Tracking Study of Integrative Spatial Cognition over Diagrammatic Representations

Shimojima

Katagiri

2010

Spatial Cognition VII

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Abstract. Spatial representations, such as maps, charts, and graphs, convey different levels of information, depending on how their elements are grouped into different units of objects. Therefore, how people set boundaries to graphical objects to be interpreted and how they maintain the object boundaries during the given task are two important problems in understanding the way people utilize spatial representations for problem-solving. Table comprehension process was experimentally investigated in terms of eye gaze control behaviors when people were required to read off information distributed over large-scale objects, e.g., a row or a column, of the given table. Evidence was found that a large-scale object can be bounded by a single attentional shift to it, and that they can be retained as coherent objects for subsequent reference. These findings suggest the existence of a higher-order information processing in the comprehension of a spatial representation, based on rather intricate processes of attention management.

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“…To obtain the fixation points from the eye tracking data, a Dispersion-Threshold Identification (ID-T) approach was used [18], [19]. Note that V hand is a 2-dimensional vector obtained from the projection of the hand motion at specific time intervals t w onto the camera plane.…”

Section: Adaptive Scaling Generationmentioning

confidence: 99%

Implicit gaze-assisted adaptive motion scaling for highly articulated instrument manipulation

Gras

Leibrandt

Wisanuvej

et al. 2017

2017 IEEE International Conference on Robotics and Automation (ICRA)

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Abstract-Traditional robotic surgical systems rely entirely on robotic arms to triangulate articulated instruments inside the human anatomy. This configuration can be ill-suited for working in tight spaces or during single access approaches, where little to no triangulation between the instrument shafts is possible. The control of these instruments is further obstructed by ergonomic issues: The presence of motion scaling imposes the use of clutching mechanics to avoid the workspace limitations of master devices, and forces the user to choose between slow, precise movements, or fast, less accurate ones. This paper presents a bi-manual system using novel self-triangulating 6-degrees-of-freedom (DoF) tools through a flexible elbow, which are mounted on robotic arms. The control scheme for the resulting 9-DoF system is detailed, with particular emphasis placed on retaining maximum dexterity close to joint limits. Furthermore, this paper introduces the concept of gaze-assisted adaptive motion scaling. By combining eye tracking with hand motion and instrument information, the system is capable of inferring the user's destination and modifying the motion scaling accordingly. This safe, novel approach allows the user to quickly reach distant locations while retaining full precision for delicate manoeuvres. The performance and usability of this adaptive motion scaling is evaluated in a user study, showing a clear improvement in task completion speed and in the reduction of the need for clutching.

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Fixation identification: The optimum threshold for a dispersion algorithm

Cited by 157 publications

References 20 publications

One algorithm to rule them all? An evaluation and discussion of ten eye movement event-detection algorithms

One algorithm to rule them all? An evaluation and discussion of ten eye movement event-detection algorithms

An Eye-Tracking Study of Integrative Spatial Cognition over Diagrammatic Representations

Implicit gaze-assisted adaptive motion scaling for highly articulated instrument manipulation

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