Understanding spatial correlation in eye-fixation maps for visual attention in videos
Abstract
In this paper, we present an analysis of recorded eye-fixation data from human subjects viewing video sequences. The purpose is to better understand visual attention for videos. Utilizing the eye-fixation data provided in the CRCNS (Collaborative Research in Computational Neuroscience) dataset, this paper focuses on the relation between the saliency of a pixel and that of its direct neighbors, without making any assumption about the structure of the eye-fixation maps. By employing some basic concepts from information theory, the analysis shows substantial correlation between the saliency of a pixel and the saliency of its neighborhood. The analysis also provides insights into the structure and dynamics of the eye-fixation maps, which can be very useful in understanding video saliency and its applications.
Cite
@article{arxiv.1901.10957,
title = {Understanding spatial correlation in eye-fixation maps for visual attention in videos},
author = {Tariq Alshawi and Zhiling Long and Ghassan AlRegib},
journal= {arXiv preprint arXiv:1901.10957},
year = {2019}
}
Comments
Proceedings of IEEE International Conference on Multimedia and Expo (ICME), Seattle, WA, Nov. 2016