A game to crowdsource data for affective computing
Chek Tien Tan, Hemanta Sapkota, Daniel Rosser, Yusuf Pisan · OPUS - Open Publications of UTS Scholars (University of Technology Sydney) · 2014
This game submission describes BeFaced, a tile matching casual tablet game that enables massive crowdsourcing of facial expressions to advance affective computing. BeFaced uses state-of-theart facial expression tracking technology with dynamic difficulty adjustment to keep the player engaged and hence obtain a large and varied face dataset. FDG attendees will experience a novel affective game input interface and also investigate how the game design enables massive crowdsourcing in an extensible manner.