Researchers have developed EyeTheia, an open-source, lightweight deep learning pipeline for gaze estimation using standard webcams. The system combines landmark extraction with a convolutional neural network, offering real-time tracking suitable for browser-based experiments and clinical research. Performance evaluations on the MPIIFaceGaze dataset showed that both adapting pre-trained models and training from scratch yielded comparable results before calibration, with user-specific fine-tuning further reducing prediction errors. EyeTheia demonstrated strong agreement with a commercial tracker in a Dot-Probe task, providing a transparent and extensible solution for low-cost gaze tracking. AI
IMPACT Provides a low-cost, accessible tool for researchers and clinicians to conduct gaze-tracking studies.
RANK_REASON The cluster describes a new open-source research paper detailing a novel gaze estimation toolbox. [lever_c_demoted from research: ic=1 ai=1.0]
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