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Multi-Modal 2D and 3D Biometrics for Face Recognition

机译:用于人脸识别的多模态2D和3D生物识别技术

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摘要

Results are presented for the largest experimental study to date that investigates the comparison and combination of 2D and 3D face data for biometric recognition. To our knowledge, this is also the only such study to incorporate significant time lapse between gallery and probe image acquisition. Recognition results are presented for gallery and probe datasets of 166 subjects imaged in both 2D and 3D, with six to thirteen weeks time lapse between gallery and probe images of a given subject. Using a PCA-based approach tuned separately for 2D and for 3D, we find no statistically significant difference between the rank-one recognition rates of 83.1% for 2D and 83.7% for 3D. Using a certainty-weighted sum-of-distance approach to combining 2D and 3D, we find a multimodal rank-one recognition rate of 92.8%, which is statistically significantly greater than either 2D or 3D alone.
机译:结果是迄今为止最大的实验研究提出了调查2D和3D面部数据进行生物识别识别的比较和组合。为了我们的知识,这也是唯一在画廊和探测图像采集之间融入大量时间间隔的这种研究。识别结果显示在2D和3D中成像的166个受试者的画廊和探针数据集,在给定主题的画廊和探针图像之间有六到13周的时间流逝。使用基于PCA的方法进行单独调整2D和3D,我们在2D和3D的83.1%的识别率之间没有发现统计学上显着差异。使用确定的加权距离方法来组合2D和3D,我们发现多模式等级 - 一个识别率为92.8%,其单独统计学显着大于2D或3D。

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