基于方差滤波和ICA算法的人眼定位
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国家自然基金(61005084);教育部高等教育博士点基金(20114307120032);湖南省教育厅科技项目(11C0076)


Eye Location Based on Variance Filter and Independent Component Analysis
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    摘要:

    采用方差滤波器确定人眼候选区域, 结合独立成分分析(ICA)方法对人眼进行快速定位, 能够有效地提取训练图像的高阶统计特征, 很好地去除基向量的相关性. 与主成分分析(PCA)和传统ICA方法相比具有更好的鉴别能力. 实验表明, 该方法的识别率可达97.3%, 并对光照和姿态变化也具有很好的鲁棒性.

    Abstract:

    A new algorithm for eye location is presented. In this method, the probable eyes candidate regions are localized rapidly by using the combination of the variance filter and the independent analysis (ICA) method. The method depends on higher-order statistics of the training images decorrelated by basis vectors. Compared with principal component analysis (PCA) and traditional method of independent component analysis, the method does better in the eye identification. The results of experiments show that the proposed method has the detection rate of 97.3%, and is more efficient and robust to the variable postures and illuminations.

    参考文献
    1 Gao Y, Wang Y. Precise eye location using Dempster-Shafer theory. Journal of Wavelets, Multiresolution and Information Processing, 2007,5(1):129-143.
    2 Valenti R, Gevers T. Accurate eye center location through invariant isocentric patterns. IEEE Trans. on Pattern Analysis and Machine Intelligence, 2012,34(9):1785-1798.
    3 Hyvarinen A, Oja E. Independent component analysis: algorithm and applications. Neural Networks, 2000,13(4-5): 411-430.
    4 Hyvarinen A. Fast and robust fixed-point algorithm for independent component analysis. IEEE Trans. on Neural Networks, 1999,10(3):626-634.
    5 Feng GC, Yuen PC. Multi-cues eye detection on gray intensity image. Pattern Recognition, 2001,34(5):1033-1046.
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李政仪,冯贵玉.基于方差滤波和ICA算法的人眼定位.计算机系统应用,2013,22(4):113-115

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  • 收稿日期:2012-09-19
  • 最后修改日期:2012-11-12
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