Saliency3D: a 3D Saliency Dataset Collected on Screen
Yao Wang, Qi Dai, Mihai Bâce, Karsten Klein, Andreas Bulling
Proc. ACM International Symposium on Eye Tracking Research and Applications (ETRA), pp. 1–9, 2024.
Abstract
While visual saliency has recently been studied in 3D, the experimental setup for collecting 3D saliency data can be expensive and cumbersome. To address this challenge, we propose a novel experimental design that utilizes an eye tracker on a screen to collect 3D saliency data. Our experimental design reduces the cost and complexity of 3D saliency dataset collection. We first collect gaze data on a screen, then we map them to 3D saliency data through perspective transformation. Using this method, we collect a 3D saliency dataset (49,276 fixations) comprising 10 participants looking at sixteen objects. Moreover, we examine the viewing preferences for objects and discuss our findings in this study. Our results indicate potential preferred viewing directions and a correlation between salient features and the variation in viewing directions.Links
Paper: wang24_etras.pdf
BibTeX
@inproceedings{wang24_etras,
title = {Saliency3D: a 3D Saliency Dataset Collected on Screen},
author = {Wang, Yao and Dai, Qi and B{\^a}ce, Mihai and Klein, Karsten and Bulling, Andreas},
year = {2024},
pages = {1--9},
booktitle = {Proc. ACM International Symposium on Eye Tracking Research and Applications (ETRA)},
doi = {10.1145/3649902.3653350}
}
