Crowdsourcing Gaze Data Collection

Dmitry Rudoy, Dan B. Goldman, Eli Shechtman, Lihi Zelnik-Manor

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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 selfreporting mechanism (see Figure 1). 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.
Original languageEnglish
Title of host publicationCollective Intelligence 2012
Number of pages8
StatePublished - 2012
EventCollective
Intelligence
2012
- MIT, Cambridge, United States
Duration: 18 Apr 201220 Dec 2012
http://www.ci2012.org/

Conference

ConferenceCollective
Intelligence
2012
Country/TerritoryUnited States
CityCambridge
Period18/04/1220/12/12
Internet address

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