The Impact of Age and Threshold Variation on Facial Recognition Algorithm Performance Using Images of Children
The Impact of Age and Threshold Variation on Facial Recognition Algorithm Performance Using Images of Children
复制标题
年龄和阈值变化对使用儿童图像的面部识别算法性能的影响
DOI：
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发表时间：
2018
期刊：
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通讯作者：
C. Malec
中科院分区：
文献类型：
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作者：
Dana Michalski;Sau Yee Yiu;C. Malec
在各种操作环境中，跨年龄阶段的面部识别，特别是儿童图像的面部识别仍然是一个具有挑战性的问题。然而，用儿童图像检查算法性能的研究是有限的，因为对年龄和年龄变化（即被比较图像之间的年龄差异）如何影响性能的了解很少。在操作上，可以使用基于成人图像的固定阈值，而不考虑这可能会影响儿童的表现。在比较儿童图像时，基于年龄和年龄变化的阈值变化可能是更好的方法。本文评估了商业现成 (COTS) 面部识别算法的性能，以确定年龄（0-17 岁）和年龄变化（0-10 岁）对使用固定阈值和阈值变化方法的面部图像受控操作数据集的影响。该评估表明，儿童的表现因年龄和年龄变化而存在很大差异，并且在某些操作设置中，阈值变化可能有利于对儿童进行面部识别。
Facial recognition across ageing and in particular with images of children remains a challenging problem in a wide of range of operational settings. Yet, research examining algorithm performance with images of children is limited with minimal understanding of how age and age variation (i.e., age difference between images being compared) impacts on performance. Operationally, a fixed threshold based on images of adults may be used without considering that this could impact on performance with children. Threshold variation based on age and age variation may be a better approach when comparing images of children. This paper evaluates the performance of a commercial off-the-shelf (COTS) facial recognition algorithm to determine the impact that age (0–17 years) and age variation (0–10 years) has on a controlled operational dataset of facial images using both a fixed threshold and threshold variation approach. This evaluation shows that performance of children differs considerably across age and age variation, and in some operational settings, threshold variation may be beneficial for conducting facial recognition with children.