@inproceedings{7d948a7439164921a3dae7fd11f953f8,
title = "Dynamic visual saliency modeling based on spatiotemporal analysis",
abstract = "Producing an appropriate extent of visually salient regions in video sequences is a challenging task. In this work, we propose a novel approach for modeling dynamic visual attention based on spatiotemporal analysis. Our model first detects salient points in three-dimensional video volumes, and then uses them as seeds to search the extent of salient regions in a motion attention map. To determine the extent of attended regions, the maximum entropy in the spatial domain is used to analyze the dynamics obtained from spatiotemporal analysis. The experiment results show that the proposed dynamic visual attention model can effectively detect visual saliency through successive video volumes.",
keywords = "Spatiotemporal analysis, Visual attention",
author = "Chen, {Duan Yu} and Tyan, {Hsiao Rong} and Hsiao, {Dun Yu} and Shih, {Sheng Wen} and MarkLiao, {Hong Yuan}",
year = "2008",
doi = "10.1109/ICME.2008.4607627",
language = "English",
isbn = "9781424425716",
series = "2008 IEEE International Conference on Multimedia and Expo, ICME 2008 - Proceedings",
pages = "1085--1088",
booktitle = "2008 IEEE International Conference on Multimedia and Expo, ICME 2008 - Proceedings",
note = "2008 IEEE International Conference on Multimedia and Expo, ICME 2008 ; Conference date: 23-06-2008 Through 26-06-2008",
}