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.