dc.contributor.author |
Osińska, Veslava |
dc.contributor.author |
Szalach, Adam |
dc.contributor.author |
Piotrowski, Dominik Mirosław |
dc.date.accessioned |
2024-10-23T07:18:25Z |
dc.date.available |
2024-10-23T07:18:25Z |
dc.date.issued |
2024-10-23 |
dc.identifier.uri |
http://repozytorium.umk.pl/handle/item/7064 |
dc.description |
The text was published in: 2024 Progress in Applied Electrical Engineering (PAEE), Koscielisko, Poland, 2024, pp. 1-3; Publisher: IEEE; DOI: 10.1109/PAEE63906.2024.10701449. |
dc.description.abstract |
In recent years, artificial intelligence (AI) has significantly advanced fields like computer vision, image description, and generation, proving particularly relevant in creative areas such as generative art. This research aimed to explore AI’s capabilities in creating and describing images compared to human perception. It included a comparative analysis of visual perception using eyetracking techniques in two settings: a VR art gallery created for the BITSCOPE project and a stationary ET study of individual images. The images, sourced from the BITSCOPE project’s CHIST-ERA IV collection, were initially described by an expert following specific instructions, which were then used by AI to generate corresponding images. The eyetracking study focused on key areas and gaze plot sequences, using a gaze plot similarity metric based on topology and path length, enabled by the size of the research group. |
dc.description.sponsorship |
The research is a part of project Bitscope (no. 2021/03/Y/ST6/00002) is supported by the National Science Centre, Poland, under CHIST-ERA IV programme, which has received funding from the EU Horizon 2020 Research and Innovation Programme, under Grant Agreement no. 857925. |
dc.language.iso |
eng |
dc.rights |
Attribution 4.0 Poland |
dc.rights.uri |
https://creativecommons.org/licenses/by/4.0/deed.pl |
dc.subject |
artificial intelligence |
dc.subject |
eyetracking |
dc.subject |
virtual reality |
dc.subject |
computer vision |
dc.title |
Eye tracking as a tool for analysing human -AI image interactions |
dc.type |
info:eu-repo/semantics/preprint |