TurkerGaze: Crowdsourcing Saliency with Webcam based Eye Tracking

> ./scripts/install.sh
> npm install
> npm start

Created by Pingmei Xu, Jianxiong Xiao at Princeton Vision Group.

TurkerGaze is a webcam-based eye tracking game for collecting large-scale eye tracking data via crowdourcing. It is implemented in javascript and the details were described in an arXiv tech report.

If you find TurkerGaze useful in your research, please consider citing:

@article{xu15arXiv,
    Author = {Pingmei Xu, Krista A Ehinger, Yinda Zhang, Adam Finkelstein, Sanjeev R. Kulkarni, Jianxiong Xiao},
    Title = {Rich feature hierarchies for accurate object detection and semantic segmentation},
    Booktitle = {arXiv:1504.06755},
    Year = {2015}
}

0. See a demo 0. Setup a local web server, download the folder, open 'pugazetrackr.html' to run the eye tracking task. Save the result data to a local file and visualize the result by 'visualizer.html'. 0. You can also try it here: eye tracking task visualization

1. User your own images 0. Create a .json object with two fields: 'gaze' and 'memory' like './demo/imglist.json'. 'gaze' contains the images that you want to present for free-viewing, and 'memory' contains images for the memory test. 0. Pass the path of this .json file by url parameter 'imglist'. For example, http://isun.cs.princeton.edu/TurkerGaze/pugazetrackr.html?imglist=your_imglist_url 0. Run the task!

TurkerGaze is released under the MIT License (refer to the LICENSE file for details).