Pupil Cloud - Projects and Enrichments
With Pupil Invisible eye tracking glasses it is easy for researchers to get up and running with mobile eye tracking in the real world. No setup, no calibration, and no operator required.
Pupil Invisible integrates seamlessly with Pupil Cloud to facilitate data logistics: robust uploads to secure cloud storage, recording playback, and data organization. We are really pleased to hear from our customers that this just works, the technology gets out of your way and becomes… invisible!
So, what's next? Analysis! Researchers need to make sense of all this data!
Once data collection is complete, the post-hoc analysis work begins. Typically, this requires researchers to review hours of recordings and perform an array of time-consuming manual coding tasks in order to generate visualizations and relevant data.
Our goal is to complete the pipeline and make it easy for researchers to collect, store, and analyze their eye tracking data in Pupil Cloud. Today we are really excited to introduce Projects and Enrichments in Pupil Cloud as a step towards our goal. A project is a group of recordings that can be further reviewed and annotated. Enrichments leverage the power of cloud computing and advanced algorithms to calculate high-level features on recordings within a project enabling data aggregation, visualization, and download.
We have a lot of exciting enrichments and features in the pipeline that we are excited to get in your hands. We look forward to your feedback on the new features!
A project in Pupil Cloud is the entry-point to analysis. Select a group of recordings in Drive and create a new project. Playback recordings and annotate with temporal events.
Events & Sections
Events are used to annotate interesting points in time in your recordings. Using events you can define related sections within multiple recordings. Enrichments can be calculated on those sections of interest.
Advanced users: You can add events in real-time while recording! Check out the developer docs.
Enrichments are the "heavy lifters" of Pupil Cloud. Here we implement state of the art computer vision and signal processing algorithms to enrich the raw sensor data. This allows you to aggregate and analyze data and visualize it.
The first enrichment we introduce today is the Marker Mapper. This enrichment uses markers to automatically map gaze onto an area of interest. You can automatically aggregate and visualize the data into e.g. a heatmap.
Concrete example: Use the Marker Mapper to generate a heatmap that visualizes gaze behavior on e.g. a magazine or a computer screen. The Marker Mapper automatically tracks physical markers in your scene and maps gaze onto the area of interest.