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首页> 外文会议>European Conference on Computer Vision(ECCV 2004) pt.4; 20040511-20040514; Prague; CZ >Fusion of Infrared and Visible Images for Face Recognition
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Fusion of Infrared and Visible Images for Face Recognition

机译：红外和可见光图像融合用于人脸识别

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A number of studies have demonstrated that infrared (IR) imagery offers a promising alternative to visible imagery due to it's insensitive to variations in face appearance caused by illumination changes. IR, however, has other limitations including that it is opaque to glass. The emphasis in this study is on examining the sensitivity of IR imagery to facial occlusion caused by eyeglasses. Our experiments indicate that IR-based recognition performance degrades seriously when eyeglasses are present in the probe image but not in the gallery image and vice versa. To address this serious limitation of IR, we propose fusing the two modalities, exploiting the fact that visible-based recognition is less sensitive to the presence or absence of eyeglasses. Our fusion scheme is pixel-based, operates in the wavelet domain, and employs genetic algorithms (GAs) to decide how to combine IR with visible information. Although our fusion approach was not able to fully discount illumination effects present in the visible images, our experimental results show substantial improvements recognition performance overall, and it deserves further consideration.
机译：大量研究表明，红外（IR）图像可以替代可见光图像，因为它对照明变化导致的面部外观不敏感。但是，IR还有其他限制，包括它对玻璃不透明。这项研究的重点是检查红外图像对由眼镜引起的面部阻塞的敏感性。我们的实验表明，当探针图像中存在眼镜而不是画廊图像中存在眼镜时，基于IR的识别性能会严重下降，反之亦然。为了解决IR的这种严重局限性，我们建议融合两种模式，利用基于可见的识别对眼镜的存在或不敏感的事实。我们的融合方案基于像素，在小波域中运行，并使用遗传算法（GA）决定如何将IR与可见信息结合在一起。尽管我们的融合方法无法完全消除可见图像中存在的照明效果，但我们的实验结果显示出整体上的识别性能有了实质性的改善，值得进一步考虑。

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