@inproceedings{408d61ad798e437d99a7a8a0a1daefaf,
title = "Normalized Gaussian Distance Graph Cuts for Image Segmentation",
abstract = "This paper presents a novel, fast image segmentation method based on normalized Gaussian distance on nodes in conjunction with normalized graph cuts. We review the equivalence between kernel k-means and normalized cuts. Then we extend the framework of efficient spectral clustering and avoid choosing weights in the weighted graph cuts approach. Experiments on synthetic data sets and real-world images demonstrate that the proposed method is effective and accurate.",
keywords = "image segmentation, kernel k-means, normalized cuts, normalized Gaussian distance, spectral clustering",
author = "Chengcai Leng and Wei Xu and Irene Cheng and Zhihui Xiong and Anup Basu",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 17th IEEE International Symposium on Multimedia, ISM 2015 ; Conference date: 14-12-2015 Through 16-12-2015",
year = "2016",
month = mar,
day = "25",
doi = "10.1109/ISM.2015.36",
language = "英语",
series = "Proceedings - 2015 IEEE International Symposium on Multimedia, ISM 2015",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "523--528",
booktitle = "Proceedings - 2015 IEEE International Symposium on Multimedia, ISM 2015",
}