@inproceedings{eb1a4a72ff0f41c482a86d496a63919b,
title = "Two-stage saliency detection based on continuous CRF and sparse coding",
abstract = "In the state-of-the-art saliency detection methods based on contrast priors, little attention is paid on the region smoothness constraints. The paper proposes a two-stage saliency detection method in which a smoothness prior is explicitly involved in a continuous Conditional Random Field (CRF). In stage one, we construct a continuous CRF based on the sparse codes of perceptual features on all locations, and minimize the energy of CRF to obtain discrimination maps. In stage two, we train a discriminative machine and learn the saliency maps from discrimination maps, aiming to take the human attention priors into consideration. Our experiments on MSRA-1000 show that the new method is effective against the state-of-the-art methods.",
keywords = "Continuous CRF, Saliency, Sparse coding",
author = "Qiyang Zhao and Fan Wang and Weibo Li and Baolin Yin",
note = "Publisher Copyright: {\textcopyright} Springer-Verlag Berlin Heidelberg 2014.; 6th Chinese Conference on Pattern Recognition, CCPR 2014 ; Conference date: 17-11-2014 Through 19-11-2014",
year = "2014",
doi = "10.1007/978-3-662-45646-0\_47",
language = "英语",
series = "Communications in Computer and Information Science",
publisher = "Springer Verlag",
pages = "455--463",
editor = "Shutao Li and Yaonan Wang and Chenglin Liu",
booktitle = "Pattern Recognition - 6th Chinese Conference, CCPR 2014, Proceedings",
address = "德国",
}