How to program a computer to recognise a bar of soap

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How does our eyesight allow us to distinguish between butter and cheese or recognise a bar of soap just from its appearance? These are the types of question posed by researchers at the computer science faculty at the Harvard School of Engineering and Applied Sciences (SEAS) in their work on computer graphics and artificial vision. The researchers are aiming to narrow the gap between ‘virtual’ and ‘real’, and make computer-generated images and digital film appear more lifelike.

Todd Zickler, the William and Ami Kuan Danoff Professor of Electrical Engineering and Computer Science at SEAS, is leading a project trying to find better ways to mimic the appearance of translucent objects, such as a bar of soap. Zickler will present his research paper this week at SIGGRAPH 2013, the International Conference and Exhibition on Computer Graphics and Interactive Techniques.

The paper elucidates how humans perceive and recognise real objects and how software can exploit the details of that process to make the most realistic computer-rendered images possible.

‘If I put a block of butter and a block of cheese in front of you, and they’re the same colour, and you’re looking for something to put on your bread, you know which is which,’ said Zickler. ‘The question is, how do you know that? What in the image is telling you something about the material?’

His hope is to eventually understand these properties well enough to instruct a computer with a camera to identify what material an object is made of and to know how to properly handle it – how much it weighs or how much pressure to safely apply to it – the way humans do.

The new approach focuses on translucent materials’ phase function, part of a mathematical description of how light refracts or reflects inside an object, and, therefore, how we see what we see.

In the past, phase function shape was considered relevant to an object's translucent appearance, but formal perceptual studies had never been carried out. This is because the space of different phase functions is so vast and perceptually diverse to the human brain that modern computational tools were required to generate and analyse so many different images.

Zickler’s team took advantage of increased computational power to trim down the potential space of images to a manageable size. They first rendered thousands of computer-generated images of one object with different computer-simulated phase functions, so each image’s translucency was slightly different from the next. From there, a program compared each image’s pixel colours and brightness to another image in the space and decided how different the two images were. Through this process, the software created a map of the phase function space according to the relative differences of image pairs, making it easy for the researchers to identify a much smaller set of images and phase functions that were representative of the whole space.

Finally, the researchers asked people to compare these representative images and judge how similar or different they were, shedding light on the properties that help us decide which objects are plastic and which are soap simply by looking at them.

‘This study, aiming to understand the appearance space of phase functions, is the tip of the iceberg for building computer vision systems that can recognise materials,’ said Zickler. The next step in this research will involve finding ways to accurately measure a material’s phase functions instead of making them up computationally, and Zickler's team is already making progress on this, with a new system that will be presented at SIGGRAPH Asia in December.

Zickler’s coauthors were Ioannis Gkioulekas, a graduate student at Harvard SEAS; Bei Xiao and Edward Adelson of MIT; and Shuang Zhao and Kavita Bala of Cornell University.

Zickler is also involved in a second study being presented at SIGGRAPH 2013 investigating 3D displays. The researchers have developed a new type of screen hardware that displays different images when lit or viewed from different directions.

By creating tiny grooves of varying depths across the screen’s surface, Zickler’s team created optical interference effects that cause the thin surface to look different when illuminated or viewed from different angles.

In the future, this work could enable multi-view, lighting-sensitive displays, where a viewer rotating around a flat surface could perceive a 3D object while looking at the surface from different angles, and where the virtual object would correctly respond to external lighting.

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