论文标题
大型数据库实时面部识别的平行方法
A Parallel Approach for Real-Time Face Recognition from a Large Database
论文作者
论文摘要
我们提出了一个能够识别一个人的新面部识别系统，只要他们以前已将其相似性存储在系统中。该系统基于存储和比较主题的面部嵌入，并在以后在实时视频提要中识别它们。该系统非常准确，并且能够实时使用其ID标记。即使使用并行化搜索技术，即使使用包含数千个面部嵌入的数据库，也能够做到这一点。这使系统非常快，并且可以高度扩展。
We present a new facial recognition system, capable of identifying a person, provided their likeness has been previously stored in the system, in real time. The system is based on storing and comparing facial embeddings of the subject, and identifying them later within a live video feed. This system is highly accurate, and is able to tag people with their ID in real time. It is able to do so, even when using a database containing thousands of facial embeddings, by using a parallelized searching technique. This makes the system quite fast and allows it to be highly scalable.
