Pin-Sung Ku, Te-Yen Wu, Ericka Andrea Valladares Bastias, Mike Y. Chen
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Wink it: investigating wink-based interactions for smartphones
Commodity mobile devices have front-facing cameras that can be used to precisely track facial expressions, such as winking, which can provide an additional input modality that co-exists with touchscreen input. We evaluate and compare three types of wink-based interactions: single wink, double wink, and long wink, in three mobile usage scenarios: sitting, walking, and lying down. Results show that single wink has similar error rate as touch input, and is preferred over touch input for targets in corner regions on a smartphone.
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