AI to identify similar materials in images
A machine-learning model can identify all the pixels in an image that represent a given material
A robot manipulating objects while, say, working in a kitchen, will benefit from understanding which items are composed of the same materials. With this knowledge, the robot would know to exert a similar amount of force whether it picks up a small pat of butter from a shadowy corner of the counter or an entire stick from inside the brightly lit fridge.
Identifying objects in a scene that are composed of the same material, known as material selection, is an especially challenging problem for machines because a material’s appearance can vary drastically based on the shape of the object or lighting conditions.
Scientists at MIT and Adobe Research have taken a step toward solving this challenge. They developed a technique that can identify all pixels in an image representing a given material, which is shown in a pixel selected by the user.
“Knowing what material you are interacting with is often quite important. Although two objects may look similar, they can have different material properties. Our method can facilitate the selection of all the other pixels in an image that are made from the same material,” says Prafull Sharma, an electrical engineering and computer science graduate student and lead author of a paper on this technique.
Read more about the MIT and Adobe Research
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