Our goal is to develop next-generation human-machine interfaces that offer human-like interactive capabilities. To this end, we research fundamental computational methods as well as ambient and on-body systems to sense, model, and analyse everyday non-verbal human behavior and cognition.
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Spotlight
- ComCo'19: Predicting Gaze Patterns: Text Saliency for Integration into Machine Learning Tasks
- ETRA'19: PrivacEye: Privacy-Preserving Head-Mounted Eye Tracking Using Egocentric Scene Image and Eye Movement Features
- ETRA'19: Privacy-Aware Eye Tracking Using Differential Privacy
- MobileHCI'18: Forecasting User Attention During Everyday Mobile Interactions Using Device-Integrated and Wearable Sensors
- MobileHCI'18: The Past, Present, and Future of Gaze-enabled Handheld Mobile Devices: Survey and Lessons Learned
- CHI'18: Which one is me? Identifying Oneself on Public Displays
- ETRA'18: Error-Aware Gaze-Based Interfaces for Robust Mobile Gaze Interaction
- ETRA'18: Learning to Find Eye Region Landmarks for Remote Gaze Estimation in Unconstrained Settings
- IMWUT'17: InvisibleEye: Mobile Eye Tracking Using Multiple Low-Resolution Cameras and Learning-Based Gaze Estimation
- UIST'17: Everyday Eye Contact Detection Using Unsupervised Gaze Target Discovery
- MUM'17: They are all after you: Investigating the Viability of a Threat Model that involves Multiple Shoulder Surfers
- CVPR'17: Gaze Embeddings for Zero-Shot Image Classification