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  1. New software turns webcams into eye-trackers

New software turns webcams into eye-trackers

Scientists have developed a software that turns computer webcams into eye-trackers, an advance that may help developers optimise content and make websites more user-friendly.

By: | Washington | Published: June 2, 2016 3:58 PM
The model assumes that a user looks at the spot where they click, so each click tells the model what the eye looks like when it's viewing a particular spot. (Reuters) The model assumes that a user looks at the spot where they click, so each click tells the model what the eye looks like when it’s viewing a particular spot. (Reuters)

Scientists have developed a software that turns computer webcams into eye-trackers, an advance that may help developers optimise content and make websites more user-friendly.

The software, called WebGazer.js, can infer where on a webpage a user is looking and can be added to any website with just a few lines of code and runs on the user’s browser.

The user’s permission is required to access the webcam, and no video is shared. Only the location of the user’s gaze is reported back to the website in real time.

“We see this as a democratisation of eye-tracking,” said Alexandra Papoutsaki, a graduate student at Brown University in the US, who led the development of the software.

“Anyone can add WebGazer to their site and get a much richer set of analytics compared to just tracking clicks or cursor movements,” said Papoutsaki.

The use of eye tracking for web analytics is not new, but such studies nearly always require standalone eye-tracking devices that often cost tens of thousands of dollars.

The studies are generally done in a lab setting, with users forced to hold their heads a certain distance from a monitor or wear a headset.

“We’re using the webcams that are already integrated in users’ computers, which eliminates the cost factor,” Papoutsaki said.

“And it’s more naturalistic in the sense that we observe people in the real environment instead of in a lab setting,” she said.

The software employs a face-detection library to locate the user’s face and eyes. It converts the image to black and white to distinguish the whites of the eyes from the iris.

Having located the iris, the system employs a statistical model that is calibrated by the user’s clicks and cursor movements.

The model assumes that a user looks at the spot where they click, so each click tells the model what the eye looks like when it’s viewing a particular spot.

It takes about three clicks to get a reasonable calibration, after which the model can accurately infer the location of the user’s gaze in real time.

Researchers performed a series of experiments to evaluate the system. They showed that it can infer gaze location within 100 to 200 screen pixels.

“That’s not as accurate as specialised commercial eye trackers, but it still gives you a very good estimation of where the user is looking,” Papoutsaki said.

The tool may help website owners to prioritise popular or eye-catching content, optimise a page’s usability, as well as place and price advertising space, researchers said.

As the team continues to refine the software, they envision broader potential applications down the road – perhaps in eye-controlled gaming or helping people with physical impairments to navigate the web.

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