BeFaced: A casual game to crowdsource facial expressions in the wild

Tan, CT; Sapkota, H; Rosser, D

BeFaced: A casual game to crowdsource facial expressions in the wild

Tan, CT Sapkota, H Rosser, D

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Publication Type:: Conference Proceeding
Citation:: Conference on Human Factors in Computing Systems - Proceedings, 2014, pp. 491 - 494
Issue Date:: 2014-01-01

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Field	Value	Language
dc.contributor.author	Tan, CT	en_US
dc.contributor.author	Sapkota, H	en_US
dc.contributor.author	Rosser, D	en_US
dc.date.issued	2014-01-01	en_US
dc.identifier.citation	Conference on Human Factors in Computing Systems - Proceedings, 2014, pp. 491 - 494	en_US
dc.identifier.isbn	9781450324748	en_US
dc.identifier.uri	http://hdl.handle.net/10453/41917
dc.description.abstract	Creating good quality image databases for affective computing systems is key to most computer vision research, but is unfortunately costly and time-consuming. This paper describes BeFaced, a tile matching casual tablet game that enables massive crowdsourcing of facial expressions to advance facial expression analysis. BeFaced uses state-of-the-art facial expression tracking technology with dynamic difficulty adjustment to keep the player engaged and hence obtain a large and varied face dataset. CHI attendees will be able to experience a novel game interface that uses the iPad's front camera to track and capture facial expressions as the primary player input, and also investigate how the game design in general enables massive crowdsourcing in an extensible manner.	en_US
dc.relation.ispartof	Conference on Human Factors in Computing Systems - Proceedings	en_US
dc.relation.isbasedon	10.1145/2559206.2574773	en_US
dc.title	BeFaced: A casual game to crowdsource facial expressions in the wild	en_US
dc.type	Conference Proceeding
utslib.for	080602 Computer-Human Interaction	en_US
utslib.for	080104 Computer Vision	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Software
pubs.organisational-group	/University of Technology Sydney/Strength - HCTD - Human Centred Technology Design
utslib.copyright.status	open_access
pubs.publication-status	Published	en_US

Abstract:

Creating good quality image databases for affective computing systems is key to most computer vision research, but is unfortunately costly and time-consuming. This paper describes BeFaced, a tile matching casual tablet game that enables massive crowdsourcing of facial expressions to advance facial expression analysis. BeFaced uses state-of-the-art facial expression tracking technology with dynamic difficulty adjustment to keep the player engaged and hence obtain a large and varied face dataset. CHI attendees will be able to experience a novel game interface that uses the iPad's front camera to track and capture facial expressions as the primary player input, and also investigate how the game design in general enables massive crowdsourcing in an extensible manner.

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http://hdl.handle.net/10453/41917