The software employs a face-detection library to locate the user's face and eyes.
New York:
A new software developed by scientists at the Brown University in the US can help website owners and developers to determine which page or content a visitor is looking at.
The software, called WebGazer.js, turns integrated computer webcams into eye-trackers that can infer where on a webpage a user is looking and can be added to any website.
The user's permission is required to access the webcam, no video is shared and 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 Brown University graduate student 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," Papoutsaki added.
When the code of the software is embedded on a website, it prompts users to give permission to access their webcams. Once permission is given, the software employs a face-detection library to locate the user's face and eyes.
The system converts the image to black and white, which enables it to distinguish the sclera (the whites of the eyes) from the iris.
"We are using the webcams that are already integrated in users' computers, which eliminates the cost factor," Papoutsaki said, adding, "It is more naturalistic in the sense that we observe people in the real environment instead of in a lab setting."
Papoutsaki and her colleagues will present a paper describing the software at the International Joint Conference on Artificial Intelligence to be held in New York from July 9-15.
The software, called WebGazer.js, turns integrated computer webcams into eye-trackers that can infer where on a webpage a user is looking and can be added to any website.
The user's permission is required to access the webcam, no video is shared and 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 Brown University graduate student 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," Papoutsaki added.
When the code of the software is embedded on a website, it prompts users to give permission to access their webcams. Once permission is given, the software employs a face-detection library to locate the user's face and eyes.
The system converts the image to black and white, which enables it to distinguish the sclera (the whites of the eyes) from the iris.
"We are using the webcams that are already integrated in users' computers, which eliminates the cost factor," Papoutsaki said, adding, "It is more naturalistic in the sense that we observe people in the real environment instead of in a lab setting."
Papoutsaki and her colleagues will present a paper describing the software at the International Joint Conference on Artificial Intelligence to be held in New York from July 9-15.
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