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周志华

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期刊论文

Face recognition with one training image per person

周志华Jianxin Wu Zhi-Hua Zhou*

Pattern Recognition Letters 23 (2002) 1711-1719,-0001,():

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摘要/描述

At present there are many methods that could deal well with frontal view face recognition. However, most of them cannot work well when there is only one training image per person. In this paper, an extension of the eigenface technique, i.e. projection-combined principal component analysis, (PC) 2A, is proposed. (PC) 2A combines the original face image with its horizontal and vertical projections and then performs principal component analysis on the enriched version of the image. It requires less computational cost than the standard eigenface technique and experimental results show that on a gray-level frontal view face database where each person has only one training image, (PC)2A achieves 3-5% higher accuracy than the standard eigenface technique through using 10-15% fewer eigenfaces.

版权说明:以下全部内容由周志华上传于   2005年08月02日 17时40分10秒,版权归本人所有。

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