@inproceedings{6af4b216900c437380daa33a6e2ea4b3,
title = "Bilinear Feature Line Analysis for Face Recognition",
abstract = "A novel Bilinear Feature Line Analysis (BFLA) is proposed for image feature extraction in this letter. Neaerest feature line (NFL) is a powerful classifier. Some NFL based subspace algorithms have been introduced recently. In most of the classical NFL-based subspace learning approaches, the input samples are vectors. For face recognition, face samples should be transformed to vectors firstly. This process induces a high computational complexity and also may lead to the loss of the geometric feature of samples. The proposed BFLA is a matrix-based algorithm. It aims to minimize the within class scatter based on two-dimensional NFL. The experimental results on Yale face databases confirm its effectiveness.",
keywords = "Bilinear transformation, Image feature extraction, Nearest feature line",
author = "Lijun Yan and Jianhui Zhang and Pan, \{Jeng Shyang\} and Linlin Tang",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 11th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIH-MSP 2015 ; Conference date: 23-09-2015 Through 25-09-2015",
year = "2016",
month = feb,
day = "19",
doi = "10.1109/IIH-MSP.2015.94",
language = "英语",
series = "Proceedings - 2015 International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIH-MSP 2015",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "286--289",
editor = "Jeng-Shyang Pan and Ching-Yu Yang and Hsiang-Cheh Huang and Ivan Lee",
booktitle = "Proceedings - 2015 International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIH-MSP 2015",
address = "美国",
}