通过剪枝改进识别:以人脸识别和身体软生物识别为例

2012 13th International Workshop on Image Analysis for Multimedia Interactive Services Pub Date : 2012-05-23 DOI:10.1109/WIAMIS.2012.6226747

Carmelo Velardo, J. Dugelay

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引用次数: 15

摘要

我们研究了身体软生物识别功能，以执行硬生物识别数据库的修剪，提高检索速度和准确性。我们基于人体测量的预分类步骤在一个大规模的医学数据集上进行了阐述，以保证结果的统计意义，并与人脸识别算法一起进行了测试。我们的假设是通过在嵌合体数据集上测试我们的系统来验证的。我们清楚地确定了取舍之间的修剪，精度和测量误差的人为测量为基础的系统。即使在最坏的情况下，人体测量偏差为±10%，我们的方法也可以提高识别精度，保证只需要考虑一半的数据库。

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Improving identification by pruning: A case study on face recognition and body soft biometric

We investigate body soft biometrics capabilities to perform pruning of a hard biometrics database improving both retrieval speed and accuracy. Our pre-classification step based on anthropometric measures is elaborated on a large scale medical dataset to guarantee statistical meaning of the results, and tested in conjunction with a face recognition algorithm. Our assumptions are verified by testing our system on a chimera dataset. We clearly identify the trade off among pruning, accuracy, and mensuration error of an anthropomeasure based system. Even in the worst case of ±10% biased anthropometric measures, our approach improves the recognition accuracy guaranteeing that only half database has to be considered.

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2012 13th International Workshop on Image Analysis for Multimedia Interactive Services

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