@inproceedings{3efb4bfdb4284bc985ed6dc929ea62aa,
title = "Saliency analysis based on depth contrast increased",
abstract = "Humans can understand their surroundings by an additional depth cue that provides by stereopsis, which plays an important role in the human visual system. Recently, depth saliency has been attracted much attention. But depth image differs a lot from color image. Feature extraction in depth image is an important problem in depth saliency analysis. Previous studies always extract features from depth map directly. This paper proposes a method which can make the saliency analysis easier and more accurate by increasing the depth contrast between the salient object and distractors. Then, we extended a recent saliency analysis approach to evaluate the saliency of the difference map. Finally, after the optimization by depth information and color information the final saliency map can be obtained. Our experiments on public dataset show that our method significantly outperforms state-of-the-art.",
keywords = "depth information, increased depth contrast, saliency detection",
author = "Hao Sheng and Xiaoyu Liu and Shuo Zhang",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 41st IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 ; Conference date: 20-03-2016 Through 25-03-2016",
year = "2016",
month = may,
day = "18",
doi = "10.1109/ICASSP.2016.7471896",
language = "英语",
series = "ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1347--1351",
booktitle = "2016 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 - Proceedings",
address = "美国",
}