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Facial Gesture Recognition: A Novel HCI model. Mentees: Chun Yang, Rishi Ratan Mentor: Sanketh Shetty. Overview. What is facial gesture recognition? Methodology Applications. Last Semester. Methodology. Use OpenCV to isolate faces in video Find a way to detect facial motion
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Facial Gesture Recognition: A Novel HCI model Mentees: Chun Yang, Rishi Ratan Mentor: Sanketh Shetty
Overview What is facial gesture recognition? Methodology Applications
Methodology • Use OpenCV to isolate faces in video • Find a way to detect facial motion - Optical Flow - Phase Correlation • Classify results from motion detection using support vector machines
Optical Flow • Estimate apparent motion in two consecutive frames • Find feature points in frame • Track the features from one frame to the next • Motion can be inferred from the movement of feature points
Optical Flow • Flaws: • Susceptible to noise • Good feature points rely on presence of edges; lack of edges on face degrades the method's effectiveness
Phase Correlation • Utilize Fast Fourier Transforms (FFT) to compute translational offsets • Apply Hamming window to reduce spectral leakage • Calculate DFT of two frames and obtain the cross-power spectrum • Normalize and apply inverse Fourier transform • Peaks in result of IDFT correspond to offsets
Phase Correlation (0, -16)
Support Vector Machines • Given an input consisting of labels and data, draw a hyperplane that maximizes the margin between two sets of data
Future Work/Applications • Effectiveness of phase correlation in facial gesture recognition can be explored further • Facial gestures could be used as a new HCI model in video games and immersive environments • Opera Web Browser Face Gestures • Method could be used in vehicles to alert drivers who are about to fall asleep
Acknowledgments • We would like to thank: • Prof. Brunet and the PURE Committee. • Our mentor Sanketh Shetty • Finally YOU, for being so considerate. Questions/Comments?