Crowdsourcing Gaze Data Collection
Collective Intelligence 2012
Dmitry Rudoy, Technion
Lihi Zelnik-Manor, Technion
Dan B Goldman, Adobe
Eli Shechtman, Adobe
Abstract
Knowing where people look is a useful tool in many various image and video applications. However, traditional gaze tracking hardware is expensive and requires local study participants, so acquiring gaze location data from a large number of participants is very problematic. In this work we propose a crowdsourced method for acquisition of gaze direction data from a virtually unlimited number of participants, using a robust self-reporting mechanism. Our system collects temporally sparse but spatially dense points-of-attention in any visual information. We apply our approach to an existing video data set and demonstrate that we obtain results similar to traditional gaze tracking. We also explore the parameter ranges of our method, and collect gaze tracking data for a large set of YouTube videos.
References
The DIEM Project (Dynamic Images and Eye Movements), http://thediemproject.wordpress.com/
Live demo
To try the system go to: Live Demo
The entire live demo takes only several minutes. It consists of two parts: a short tutorial session and video experiment. In the end you will be presented your results compared to the data collected in our experiments.
@inproceedings{rudoycrowdsourcing,
author = {Dmitry Rudoy and
Dan B Goldman and
Eli Shechtman and
Lihi Zelnik-Manor},
title = {Crowdsourcing Gaze Data Collection},
booktitle = {Collective Intelligence},
year = {2012},
}