Emotion recognition via facial expression and body pose
A subject’s facial expressions and body poses can be used to infer his/her emotional state. Automated recognition of emotion from facial expression and/or body poses can play a significant role in human-computer interaction (HCI), which has helped to create meaningful and responsive HCI interfaces. It has also been used in behavioural study, video games, animations, and safety mechanism in automobiles. I’m interested in supervising PhD research in creating a robust HCI interface (involving automated emotion recognition that takes both facial expressions and body poses as inputs) that can adapt the interaction with a practical application.
Gait analysis for human identification
Biometrics has emerged as a reliable means of identifying a human subject based on the subject's distinctive biological features. Behavioural biometrics examines human behaviour and the most promising example is gait that exploits a subject's distinctive way of walking to perform identification. Gait analysis has a wide range of applications in surveillance for security, forensics and biometric authentication. Silhouette-based gait recognition methods do not assume an explicit model of the human body, but analyse the spatio-temporal shape and motion characteristics of silhouettes. I am interested in supervising a PhD research in silhouette-based 3D gait analysis (for view invariance).
Other research topics
I am also interested in supervising PhD research in the following topics: enhancement of video sequences; 3-dimensional object reconstruction from images via shape from silhouettes (SfS) or via structure from motion (SfM); autonomous navigation in a multiscale framework; real-time hand tracking; digital sculpturing; and face verification.
Note: Should your application for admission be accepted you should be aware that this does not constitute an offer of financial support. Please refer to the scholarships & funding pages.