Robust eye centers localization with zero-crossing encoded image projections
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- 作者：Laura Florea ; Corneliu Florea ; Constantin Vertan
- 关键词：Eye localization ; Image projections ; Zero ; crossing encoding ; Real time
- 刊名：Pattern Analysis and Applications
- 出版年：2017
- 出版时间：February 2017
- 年：2017
- 卷：20
- 期：1
- 页码：127-143
- 全文大小：
- 刊物类别：Computer Science
- 刊物主题：Pattern Recognition;
- 出版者：Springer London
- ISSN：1433-755X
- 卷排序：20
文摘
This paper proposes a new framework for the eye centers localization by the joint use of encoding of normalized image projections and a multi-layer perceptron (MLP) classifier. The encoding is novel and it consists in identifying the zero-crossings and extracting the relevant parameters from the resulting modes. The compressed normalized projections produce feature descriptors that are inputs to a properly trained MLP, for discriminating among various categories of image regions. The proposed framework forms a fast and reliable system for the eye centers localization, especially in the context of face expression analysis in unconstrained environments. We successfully test the proposed method on a wide variety of databases including BioID, Cohn–Kanade, Extended Yale B and Labeled faces in the wild databases.