Pupil: An Open Source Platform for Pervasive Eye Tracking and Mobile Gaze-based Interaction
arXiv:1405.0006
Abstract
Commercial head-mounted eye trackers provide useful features to customers in industry and research but are expensive and rely on closed source hardware and software. This limits the application areas and use of mobile eye tracking to expert users and inhibits user-driven development, customisation, and extension. In this paper we present Pupil -- an accessible, affordable, and extensible open source platform for mobile eye tracking and gaze-based interaction. Pupil comprises 1) a light-weight headset with high-resolution cameras, 2) an open source software framework for mobile eye tracking, as well as 3) a graphical user interface (GUI) to playback and visualize video and gaze data. Pupil features high-resolution scene and eye cameras for monocular and binocular gaze estimation. The software and GUI are platform-independent and include state-of-the-art algorithms for real-time pupil detection and tracking, calibration, and accurate gaze estimation. Results of a performance evaluation show that Pupil can provide an average gaze estimation accuracy of 0.6 degree of visual angle (0.08 degree precision) with a latency of the processing pipeline of only 0.045 seconds.
10 pages, 9 figures
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- Head and eye egocentric gesture recognition for human-robot interaction using eyewear cameras
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- Gaze-enhanced Crossmodal Embeddings for Emotion Recognition
- GazeDPM: Early Integration of Gaze Information in Deformable Part Models
- MPIIGaze: Real-World Dataset and Deep Appearance-Based Gaze Estimation
- ESCaF: Pupil Centre Localization Algorithm with Candidate Filtering
- Adversarial Attacks on Classifiers for Eye-based User Modelling
- Personalized Image-based User Authentication using Wearable Cameras
- Robust Video-Based Eye Tracking Using Recursive Estimation of Pupil Characteristics