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2012

Crowdsourcing Gaze Data Collection

Rudoy, Dmitry, Goldman, Dan B., Shechtman, Eli et al.

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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 (see Figure 1).
Our system collects temporally sparse but spatially dense points-of-attention in any visual information.

Crowdsourcing Gaze Data Collection · Around

Built on

[] Rele, R. & Duchowski, A. (2005), Using eye tracking to evaluate alternative search results interfaces, in
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[] Goldstein, R., Woods, R. & Peli, E. (2007), ‘Where people look when watching movies: Do all viewers look at the same place?’, Computers in biology and medicine
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[] Smith, T. & Henderson, J. (2008), ‘Edit blindness: The relationship between attention and global change blindness in dynamic scenes’, Journal of Eye Movement Research
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Similar

[] Judd, T., Ehinger, K., Durand, F. & Torralba, A. (2009), Learning to predict where humans look, in
2009
Cited alongside, same era.
[] Nataraju, S., Balasubramanian, V. & Panchanathan, S. (2009), Learning attention based saliency in videos from human eye movements, in
2009
Cited alongside, same era.
http://eyetracking-glasses.com
[] SensoMotoric Instruments (n.d.), ‘Smi eye tracking glasses’
Cited in the paper.

Then

http://www.sr-research.com
[] EyeLink (2010), ‘SR Research’ · 2010
Later among the works it cites.
[] Mital, P., Smith, T., Hill, R. & Henderson, J. (2010), ‘Clustering of gaze during dynamic scene viewing is predicted by motion’, Cognitive Computation
2010
Later among the works it cites.

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