| Autor: |
Tauhidur Rahman, Soha Rostaminia, Subhransu Maji, Deepak Ganesan, Alexander Lamson |
| Rok vydání: |
2019 |
| Předmět: |
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| Zdroj: |
ETRA |
| Popis: |
The ability to unobtrusively and continuously monitor one's facial expressions has implications for a variety of application domains ranging from affective computing to health-care and the entertainment industry The standard Facial Action Coding System (FACS) along with camera based methods have been shown to provide objective indicators of facial expressions; however, these approaches can also be fairly limited for mobile applications due to privacy concerns and awkward positioning of the camera. To bridge this gap, W!NCE re-purposes a commercially available Electrooculography-based eyeglass (J!NS MEME) for continuously and unobtrusively sensing of upper facial action units with high fidelity. W!NCE detects facial gestures using a two-stage processing pipeline involving motion artifact removal and facial action detection. We validate our system's applicability through extensive evaluation on data from 17 users under stationary and ambulatory settings. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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