WebGazer.js - Eye-tracking library for common webcams
Description
WebGazer.js an online eye tracker that uses common webcams already present in laptops and mobile devices to infer the eye-gaze locations of web visitors on a page in real time. With this it e a natural experience to
everyday users that is not restricted to laboratories and highly controlled user studies. WebGazer.js has two key components: a pupil detector that can be combined with any eye detection library, and a gaze estimator using regression analysis informed by user interactions.
Advantages of WebGazer.js:
- Real time gaze prediction on most major browsers
- Self-calibration from clicks and cursor movements
- Easy to integrate with a few lines of JavaScript
- Swappable components for eye detection
- Multiple gaze prediction models
URL:
- https://webgazer.cs.brown.edu/#home
- http://jeffhuang.com/Final_WebGazer_IJCAI16.pdf
- https://github.com/brownhci/WebGazer
Prerequisites for using this software - Software/Hardware : No special hardware - WebGazer.js uses common webcams
Project Anatomy
Community: Alexandra Papoutsaki, James Laskey, Aaron Gokaslan, Yuze He, Jeff Huang.
Leadership: Dr. Gerald Weber and his team Dr. Clemens Zeidler and Kai-Cheung Leung
Forking: Fork your own copy at this address: https://github.com/brownhci/WebGazer, for which you will need a GitHub account.
Communication: There is info for contact on the personal profiles of two members, Alexandra Papoutsaki: http://www.cs.pomona.edu/~apapoutsaki/ and Jeff Huang: http://jeffhuang.com/.
Roadmaps:
Original goal:
It was designed as a new approach to browser-based eye tracking for common webcams.
Future goals:
Short term:
WebGazer.js aims to overcome the accuracy problems that webcams typically face, by adopting user interactions to continuously self-calibrate during regular web browsing.
Releases:
- WebGazer: Scalable Webcam Eye Tracking Using User Interactions - Alexandra Papoutsaki, Nediyana Daskalov, Patsorn Sangkloy, Jeff Huang, James Laskey, James Hays - July 2016 Conference: 25th International Joint Conference on Artificial Intelligence (IJCAI 2016)At: New York City, New York
Repositories:
The main repository of WebGazer.js is: https://github.com/brownhci/WebGazer , where you can download the source code, clone it to desktop, or even make your own fork.
Packaging:
It exists only one version, available at: https://webgazer.cs.brown.edu/#download
Upstream/downstream:
So far, from 2016 when it was originaly published, WebGazer.js has 14 contibutors, and it is open for contributing for upstream, after of course your pull request is revised and approved.
Version Control:
Latest version control is nowhere specified.
Trackers:
You can see commits and verified changes through the existing and solved issues at this link: https://github.com/brownhci/WebGazer/issues.
Project Evaluation
Fieldtrips
Github: https://github.com/brownhci/WebGazer
Openhub: / (WebGazer.js is not listed here)
Source Forge: / (WebGazer.js is not listed here)
Evaluation
Licensing: GPLv3
Language: Javascript
Activity: Active
Number of contributors: There are six developers and 14 contributors. They are listed on this page: https://github.com/brownhci/WebGazer/graphs/contributors
Size: Size is not specified anywhere.
Issue tracker: There is an issue tracker on GitHub: https://github.com/brownhci/WebGazer/issues
New contributor: If you want to be a contributor to WebGazer.js one way is through the GitHub page, where you can make your own fork and pull request and wait for an approval.
Community norms: You can report an issue through the issue page , help to fix it by forking in the GitHub repository and commit fixes and if you prefer to work via different channels (contact info pages).
User base: Their user base are the developers and the contributors.
