论文标题
时间飞行：分析面部衰老对合成数据识别性能的影响
Time flies by: Analyzing the Impact of Face Ageing on the Recognition Performance with Synthetic Data
论文作者
论文摘要
合成图像合成的巨大进步使得面部图像在高分辨率和光真相中产生。在生物识别应用中，使用合成数据的主要动机是解决公共可用的生物识别数据的短缺，同时在处理此类敏感信息时降低隐私风险。这些优点在这项工作中是通过模拟人脸老化的最新面孔修饰算法来生成交配样本的，从而研究了衰老对开源生物识别识别系统的性能的影响。此外，使用真实数据集评估短期衰老的影响，将生物识别性能与合成结构域进行比较。主要发现表明，短期老化在1 - 5年的范围内仅对一般识别绩效产生较小的影响。但是，对长期年龄差异超过20岁的配对面的正确验证仍然是一个重大挑战，需要进一步调查。
The vast progress in synthetic image synthesis enables the generation of facial images in high resolution and photorealism. In biometric applications, the main motivation for using synthetic data is to solve the shortage of publicly-available biometric data while reducing privacy risks when processing such sensitive information. These advantages are exploited in this work by simulating human face ageing with recent face age modification algorithms to generate mated samples, thereby studying the impact of ageing on the performance of an open-source biometric recognition system. Further, a real dataset is used to evaluate the effects of short-term ageing, comparing the biometric performance to the synthetic domain. The main findings indicate that short-term ageing in the range of 1-5 years has only minor effects on the general recognition performance. However, the correct verification of mated faces with long-term age differences beyond 20 years poses still a significant challenge and requires further investigation.
