  Opportunistic affect sensing offers unprecedented potential for capturing
spontaneous affect ubiquitously, obviating biases inherent in the laboratory
setting. Facial expression and voice are two major affective displays, however
most affect sensing systems on smartphone avoid them due to extensive power
requirement. Encouragingly, due to the recent advent of low-power DSP (Digital
Signal Processing) co-processor and GPU (Graphics Processing Unit) technology,
audio and video sensing are becoming more feasible. To properly evaluate
opportunistically captured facial expression and voice, contextual information
about the dynamic audio-visual stimuli needs to be inferred. This paper
discusses recent advances of affect sensing on the smartphone and identifies
the key barriers and potential solutions of implementing opportunistic and
context-aware affect sensing on smartphone platforms.
