AOI scan path analyzers

ArGaze provides ready-to-use AOI scan path analysis algorithms.

Definition

An AOIScanPath defined as a list of AOIScanSteps made by a set of successive fixations/saccades onto a same AOI.

The JSON samples have to be included inside ArLayer configuration aoi_scan_path_analyzers entry to select an algorithm.

"aoi_scan_path_analyzers": {
    JSON sample
}

Read more about AOIScanPathAnalyzer base class in code reference.

Note

The members indicated as property are what returns the analyzer.

Basic metrics

Bases: GazeFeatures.AOIScanPathAnalyzer

Basic AOI scan path analysis.

aoi_fixation_distribution: dict property

percentage of time spent on each AOI.

path_duration: float property

AOI scan path duration.

step_fixation_durations_average: float property

AOI scan path step fixation durations average.

steps_number: float property

AOI scan path steps number.

JSON sample

"argaze.GazeAnalysis.Basic.AOIScanPathAnalyzer": {}

Entropy

Bases: GazeFeatures.AOIScanPathAnalyzer

Implementation of entropy algorithm as described in:

Krejtz K., Szmidt T., Duchowski A.T. (2014).
Entropy-based statistical analysis of eye movement transitions.
Proceedings of the Symposium on Eye Tracking Research and Applications (ETRA'14, 159-166).
https://doi.org/10.1145/2578153.2578176

stationary_entropy: float property

Stationary entropy.

transition_entropy: float property

Transition entropy.

transition_matrix_analyzer: TransitionMatrix.AOIScanPathAnalyzer property writable

Bind to TransitionMatrix analyzer to get its transition_matrix_probabilities.

Mandatory

TransitionMatrix analyzer have to be loaded before.

JSON sample

"argaze.GazeAnalysis.Entropy.AOIScanPathAnalyzer": {}

K-modified coefficient

Bases: GazeFeatures.AOIScanPathAnalyzer

Implementation of the K-modified coefficient algorithm as described in:

Lounis, C. A., Hassoumi, A., Lefrancois, O., Peysakhovich, V., & Causse, M. (2020, June).
Detecting ambient/focal visual attention in professional airline pilots with a modified Coefficient K: a full flight simulator study.
ACM Symposium on Eye Tracking Research and Applications (ETRA'20, 1-6).
https://doi.org/10.1145/3379157.3391412

K: float property

K coefficient.

JSON sample

"argaze.GazeAnalysis.KCoefficient.AOIScanPathAnalyzer": {}

Lempel-Ziv complexity

Bases: GazeFeatures.AOIScanPathAnalyzer

Implementation of Lempel-Ziv complexity algorithm as described in:

Lounis C., Peysakhovich V., Causse M. (2020).
Lempel-Ziv Complexity of dwell sequences: visual scanning pattern differences between novice and expert aircraft pilots.
Proceedings of the 1st International Workshop on Eye-Tracking in Aviation (ETAVI'20, 61-68).
https://doi.org/10.3929/ethz-b-000407653

lempel_ziv_complexity: int property

Lempel-Ziv complexity.

JSON sample

"argaze.GazeAnalysis.LempelZivComplexity.AOIScanPathAnalyzer": {}

N-Gram

Bases: GazeFeatures.AOIScanPathAnalyzer

Implementation of N-Gram algorithm as proposed in:

Lounis C., Peysakhovich V., Causse M. (2021).
Visual scanning strategies in the cockpit are modulated by pilots’ expertise: A flight simulator study.
PLoS ONE (16(2), 6).
https://doi.org/10.1371/journal.pone.0247061

n_max: int property writable

Maximal grams length to search.

n_min: int property writable

Minimal grams length to search.

ngrams_count: dict property

N-Grams count.

JSON sample

"argaze.GazeAnalysis.NGram.AOIScanPathAnalyzer": {
    "n_min": 3,
    "n_max": 5
}

Transition matrix

Bases: GazeFeatures.AOIScanPathAnalyzer

Implementation of transition matrix probabilities and density algorithm as described in:

Krejtz K., Szmidt T., Duchowski A.T. (2014).
Entropy-based statistical analysis of eye movement transitions.
Proceedings of the Symposium on Eye Tracking Research and Applications, (ETRA'14, 159-166).
https://doi.org/10.1145/2578153.2578176

transition_matrix_density: float property

Transition matrix density.

transition_matrix_probabilities: pandas.DataFrame property

Transition matrix probabilities

JSON sample

"argaze.GazeAnalysis.TransitionMatrix.AOIScanPathAnalyzer": {}