VOA慢速英语--AI for Fun: Machine Learning Makes Caricature Faces

 

A team of machine learning developers has created a system for making caricatures of people’s faces.

In a caricature, the artist creates a drawing of a face, with different parts of it greatly enlarged, or exaggerated, in other ways. The pictures or images are usually made to make the person look funny.

Such drawings can be difficult for machines to produce. This is often because the human face is made up of complex shapes with a lot of extremely small details. Generally, good caricatures require skilled artists who can effectively exaggerate faces, while still staying true to life.

The new system for making caricatures is the creation¹ of computer scientists from the City University of Hong Kong and Microsoft Corporation. They presented their findings at a recent computer graphics² conference in Tokyo.

Kaidi Cao led the research. He is currently³ studying computer science at Stanford University in California. He helped develop the system while working as a volunteer at Microsoft. Other members of the team were Lu Yuan of Microsoft and Jing Liao of the City University of Hong Kong.

Cao describes the process as a “photo-to-caricature translation.” He says other machine systems for creating caricatures depend on a series of rules, which are based on how people would draw. But his team’s system uses machine learning to create the caricatures from thousands of examples made by experienced artists.

In a paper explaining his research, Cao said other machine-based systems appear to pay more attention to appearance and style. But his team’s research uses a second machine learning tool to add “geometric exaggeration.”

The new method improves on existing ones “in terms of visual quality and preserving identity,” Cao wrote. In addition, the system gives users more ability to change results in both shape exaggeration and appearance, he added.

The team tested how recognizable its caricatures were to human test subjects in two separate studies.

In the first study, people were shown caricatures and then asked to choose the correct one from a group of images with faces that looked very similar.

Test results showed that in many cases, people had difficulty choosing the correct image when the caricatures were created with the older methods. The researchers said this was because such systems often created caricatures that were far too exaggerated or unclear.

Not surprisingly, the most easily recognized caricatures in the experiment were made by humans. But the researchers said their system performed better in tests with human subjects than the older methods.

The second study tested how close the system’s caricatures were to hand-made caricature styles. People were first shown eight caricatures drawn⁴ by artists. They were then presented with one hand-drawn caricature and five machine-created examples. Test subjects were then asked a series of questions about which examples were the most similar.

Results showed that people taking part in this experiment chose the team’s machine-created caricature about 23 percent of the time. This means the system “can fool users into thinking it is the real hand-drawn caricature,” the researchers wrote. The team noted⁵, however, that “an ideal fooling rate” for such a system would be about 50 percent.

To date, the team has mostly worked on developing caricatures of people’s faces. But the researchers say they plan to expand on this in the future to include full bodies and other objects.

They also plan to explore turning the current model around to permit caricature-to-photo translation. The team says it believes this might be useful for facial recognition⁶ of caricatures.

I’m Bryan Lynn.

Words in This Story

caricature – n. a funny drawing of someone that makes part of their appearance or character more noticeable than it really is

exaggerate – v. make something seem larger, better or worse than it really is

translation – n. process of changing from one form to another, such as with languages

style – n. way of doing something that is typical of a particular person, group, place, or period

geometric – adj. of, relating to, or according to the methods or principles of geometry

preserve – v. to keep something the same or prevent it from being damaged or destroyed

1 creation   

n.创造，创造的作品，产物，宇宙，天地万物

参考例句：

• Language is the most important mental creation of man.语言是人类头脑最重要的产物。
• The creation of new playgrounds will benefit the local children.新游戏场的建立将有益于当地的儿童。

2 graphics   

n.制图法，制图学；图形显示

参考例句：

• You've leveraged your graphics experience into the video area.你们把图形设计业务的经验运用到录像业务中去。
• Improved graphics took computer games into a new era.经改进的制图技术将电脑游戏带进了一个新时代。

3 currently   

adv.通常地，普遍地，当前

参考例句：

• Currently it is not possible to reconcile this conflicting evidence.当前还未有可能去解释这一矛盾的例证。
• Our contracts are currently under review.我们的合同正在复查。

4 drawn   

v.拖，拉，拔出；adj.憔悴的，紧张的

参考例句：

• All the characters in the story are drawn from life.故事中的所有人物都取材于生活。
• Her gaze was drawn irresistibly to the scene outside.她的目光禁不住被外面的风景所吸引。

5 noted   

adj.著名的，知名的

参考例句：

• The local hotel is noted for its good table.当地的那家酒店以餐食精美而著称。
• Jim is noted for arriving late for work.吉姆上班迟到出了名。

6 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。