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Compute MultiMatch Metrics for Scanpath Similarity

multi_match.Rd

This function computes multiple similarity metrics between two scanpaths, including vector, direction, length, position, duration, and EMD-based position similarity.

Usage

multi_match(x, y, screensize)

Arguments

x

A data frame representing the first scanpath. Must contain at least three columns: x, y, and onset, and at least three rows.

y

A data frame representing the second scanpath. Must contain at least three columns: x, y, and onset, and at least three rows.

screensize

A numeric vector of length 2 indicating the width and height of the screen in pixels.

Value

A named numeric vector with the following elements:

mm_vector

Similarity based on the 2D vectors between fixations.

mm_direction

Similarity based on the direction (angle) of saccades between fixations.

mm_length

Similarity based on the length of saccades between fixations.

mm_position

Similarity based on the spatial position of fixations.

mm_duration

Similarity based on the duration of fixations.

mm_position_emd

Order-insensitive similarity based on the Earth Mover's Distance (EMD) between the spatial positions of fixations.

Details

The function computes six different similarity metrics between the scanpaths x and y:

  • mm_vector: Similarity based on the 2D vectors between fixations.

  • mm_direction: Similarity based on the direction (angle) of saccades between fixations.

  • mm_length: Similarity based on the length of saccades between fixations.

  • mm_position: Similarity based on the spatial position of fixations.

  • mm_duration: Similarity based on the duration of fixations.

  • mm_position_emd: Order-insensitive similarity based on the Earth Mover's Distance (EMD) between the spatial positions of fixations.

The function ensures that both scanpaths have strictly increasing onset times and contain at least three fixations. It also normalizes the similarity scores to lie between 0 and 1, with higher values indicating greater similarity.

References

Dewhurst, R., Nyström, M., Jarodzka, H., Foulsham, T., Johansson, R., & Holmqvist, K. (2012). It depends on how you look at it: Scanpath comparison in multiple dimensions with MultiMatch, a vector-based approach. Behavior research methods, 44, 1079-1100.

Examples

if (FALSE) { # \dontrun{
# Example usage:
scanpath1 <- data.frame(x = runif(10, 0, 500), y = runif(10, 0, 500), onset = cumsum(runif(10, 1, 5)))
scanpath2 <- data.frame(x = runif(10, 0, 500), y = runif(10, 0, 500), onset = cumsum(runif(10, 1, 5)))
screensize <- c(500, 500)
similarity_scores <- multi_match(scanpath1, scanpath2, screensize)
print(similarity_scores)
} # }