The INI-30 Dataset : Event Camera for Eye Tracking
Contributors
Data collector:
Others:
Supervisors:
- 1. ETH Zurich
- 2. Deutsches Forschungszentrum für Künstliche Intelligenz GmbH
Description
The Ini-30 dataset is collected with two event cameras mounted on a glass frame. Each DVXplorer sensor (640 × 480 pixels) is attached on the side of the frame. The power supply was provided via a 2 meter cable connected from the cameras to a computer, which provided enough freedom of movement. Differently from [2, 24], the participants were not instructed to follow a dot on a screen, but rather encouraged to look around to collect natural eye movements. As shown in Fig. 1, the event cameras were securely screwed on a 3D-printed case attached to the side of the glass frame. The data was annotated based on accumulated linearly decayed events by defining the pixel intensity as function of the linear accumulation of previous pixel intensity. Next we labeled the position of the pupil in the DVS’s array manually, using an assistive labeling tool. We discarded the first 20ms of events to ensure the eye was visible and annotations met the level of image-based annotators. The number of labels per recording was intentionally variable, spanning from 475 to 1’848 with a time per label ranging from 20.0 to 235.77 milliseconds depending on the overall duration of the sample. This setup allows for unconstrained head movements, enables to capture event data from eye movement in a ”in-the-wild” setting and allows the generation of a representative, unique, diverse and challenging dataset.
Files
evs_ini30.zip
Files
(4.4 GB)
Name | Size | Download all |
---|---|---|
md5:92782145b1debd0dd7a2ade9c345eb88
|
4.4 GB | Preview Download |
Additional details
Funding
- Swiss National Science Foundation
- Neuromorphic Attention Models for Event Data (NAMED) 219943
Software
- Repository URL
- https://github.com/pbonazzi/retina
References
- Retina : Low-Power Eye Tracking with Event Camera and Spiking Hardware, Bonazzi et al., IEEE/CVF Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2024