EyeCatchingMaps

EyeCatchingMaps, a Dataset to Assess Saliency Models on Maps

Abstract

Saliency models try to predict the gaze behaviour of people in the first seconds of their observation of an image. To assess how much these models can perform to predict saliency in maps, we lack a ground truth to compare to. This paper proposes EyeCatchingMaps, an open dataset that can be used to benchmark saliency models for maps. The dataset has been obtained by recording the gaze of participants looking at different maps for 3 seconds with an eye-tracker. The use of EyeCatchingMaps is demonstrated by comparing two different saliency models from the literature to the real saliency maps derived from people’s gaze.

Full citation (dataset) with DOI

Wenclik, L., & Touya, G. (2024). EyeCatchingMaps, a Dataset to Assess Saliency Models on Maps [Data set]. Zenodo. https://doi.org/10.5281/zenodo.10619513

Wenclik, L. and Touya, G. (2024) EyeCatchingMaps, a Dataset to Assess Saliency Models on Maps, AGILE GIScience Ser., 5, 51, https://doi.org/10.5194/agile-giss-5-51-2024

https://agile-giss.copernicus.org/articles/5/51/2024/

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cartography  maps  eye-tracking  saliency 

GeoEye

BNU500 A geospatial image based eye movement dataset for cartography and GIS

Abstract

A geospatial image-based eye movement dataset called GeoEye, a publicly shared, widely available eye movement dataset. This dataset consists of 110 college- aged participants who freely viewed 500 images, including thematic maps, remote sensing images, and street view images, which could use for geospatial image saliency prediction and map user identification.

Full citation (dataset) with DOI

HE, ICE (2021). GeoEye dataset. figshare. Dataset. https://doi.org/10.6084/m9.figshare.14684214.v4

He, B., Dong, W., Liao, H., Ying, Q., Shi, B., Liu, J., & Wang, Y. (2023). A geospatial image based eye movement dataset for cartography and GIS. Cartography and Geographic Information Science, 50(1), 96–111. https://doi.org/10.1080/15230406.2022.2153172

https://www.tandfonline.com/doi/full/10.1080/15230406.2022.2153172

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eye movement dataset  geospatial image  cartography  GIS  visual saliency detection