Opportunistic and Context-aware Affect Sensing on Smartphones: The Concept, Challenges and Opportunities
February 10, 2015 Β· Declared Dead Β· π IEEE pervasive computing
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Authors
Rajib Rana, Margee Hume, John Reilly, Raja Jurdak, Jeffrey Soar
arXiv ID
1502.02796
Category
cs.HC: Human-Computer Interaction
Cross-listed
cs.CY
Citations
20
Venue
IEEE pervasive computing
Last Checked
4 months ago
Abstract
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.
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