VOA慢速英语2020--人脸识别系统对蒙面人识别能力越来越强

Study: Facial Recognition¹ Is Getting Better at Identifying People in Masks

A U.S. government study has found that facial recognition technology is getting better at identifying people wearing masks.

The study is part of ongoing² research by the U.S. Commerce Department's National Institute of Standards and Technology (NIST). The agency has examined the effectiveness of more than 150 facial recognition systems on people wearing face coverings. The systems are powered by machine learning algorithms.

The first results of the study were announced in July, as health officials across the world urged people to wear masks to limit the spread of the coronavirus. New findings were released this week.

Police agencies around the world have long used facial recognition technology to search for and help catch people accused of crimes.

It can also be used to unlock³ phones or other electronic devices, and in some cases, even vehicles. Some robots use facial recognition technology to recognize the people they are communicating with.

However, the wide use of masks in public has created major difficulties for such systems.

The study looked at facial recognition systems already in use before the pandemic. It also looked at systems specially⁴ developed to work on masked faces. Developers of the technology voluntarily provide their algorithms for testing.

The NIST said it processed a total of 6.2 million images for the experiment. These included pictures provided by individuals seeking U.S. immigration benefits, as well as images from border crossings of travelers entering the United States.

People in the images were not actually wearing masks. So, the researchers digitally added different mask shapes to faces in the pictures for use in the study. In some cases, up to 70 percent of a person's face was covered in the images.

Overall, the NIST said its research shows that the top-performing facial recognition systems fail to correctly identify unmasked individuals about 0.3 percent of the time. The failure rate rose to about 5 percent with masked images tested with the most effective systems. Many of the lower performing algorithms, however, had much higher error rates with masked images – as high as 20 to 50 percent.

In the latest findings, researchers included results from 65 new facial recognition systems that have been developed since the start of the pandemic. Some of these systems performed "significantly better" than the earlier ones, the NIST's Mei Ngan said in a statement on Tuesday. She is a lead researcher on the project.

"In the best cases, software algorithms are making errors between 2.4 and 5 percent of the time on masked faces," Ngan said. She added that this performance rate is "comparable⁵ to where the technology was in 2017 on non-masked photos."

The researchers reported that the systems were much more effective at identifying individuals when one image of the person was masked and the other was unmasked. When faces were covered in both photos, failure rates rose greatly.

Not surprisingly, the study found that round-shaped masks – which cover only the mouth and nose – led to fewer errors than wider ones that stretch across the cheeks. Also, masks covering the nose led to higher failure rates than those that did not.

The new study also ran tests to see whether different colored masks would affect error rates. The team used red, white, black and light blue. The research findings suggested that generally, the red and black masks led to higher failure rates than the other colors.

Words in This Story

mask – n. a covering used to protect your face or cover your mouth

algorithm – n. a set of steps that are followed in order to solve a mathematical problem or to complete a computer process

pandemic – n. an occurrence⁶ in which a disease spreads very quickly and affects a large number of people over a wide area or throughout the world

benefit – n. money the government gives to people who are sick, poor, unemployed⁷, etc.

digitally – adv. in a way that shows information in the form of an electronic image

overall – adj. including all the people or things in a particular group or situation

error – n. a mistake

significant – adj. important or noticeable

cheek – n. the soft part of the face below a person eye and between the mouth and ear

1 recognition   

n.承认，认可，认出，认识

参考例句：

• The place has changed beyond recognition.这地方变得认不出来了。
• A sudden smile of recognition flashed across his face.他脸上掠过一丝笑意，表示认识对方。

2 ongoing   

adj.进行中的，前进的

参考例句：

• The problem is ongoing.这个问题尚未解决。
• The issues raised in the report relate directly to Age Concern's ongoing work in this area.报告中提出的问题与“关心老人”组织在这方面正在做的工作有直接的关系。

3 unlock   

v.启示，揭示，开...的锁

参考例句：

• The border police required the traveler to unlock his luggage.边防警察要求旅客打开行李。
• We heard somebody unlock the door.我们听见有人开门锁。

4 specially   

adv.特定地；特殊地；明确地

参考例句：

• They are specially packaged so that they stack easily.它们经过特别包装以便于堆放。
• The machine was designed specially for demolishing old buildings.这种机器是专为拆毁旧楼房而设计的。

5 comparable   

adj.相似的，同类的，可比的，比得上的

参考例句：

• A fire is comparable with the sun,both give light and heat.火可以和太阳相比，两者都可以发光发热。
• No horse has a speed comparable to that of his.没有一匹马的速度能比得上他的马。

6 occurrence   

n.发生，出现，事件，发生的事件

参考例句：

• Two things account for its occurrence.发生这件事的原因有两个。
• For a military commander，winning or losing a battle is a common occurrence.胜败乃兵家常事。

7 unemployed   

adj.失业的，没有工作的；未动用的，闲置的

参考例句：

• There are now over four million unemployed workers in this country.这个国家现有四百万失业人员。
• The unemployed hunger for jobs.失业者渴望得到工作。