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diff --git a/docs/use_cases/pilot_gaze_tracking/introduction.md b/docs/use_cases/pilot_gaze_tracking/introduction.md new file mode 100644 index 0000000..7e88c69 --- /dev/null +++ b/docs/use_cases/pilot_gaze_tracking/introduction.md @@ -0,0 +1,47 @@ +Real time head-mounted eye tracking interactions +================================================ + +**ArGaze** enabled a cognitive assistant to support a pilot's situation awareness. + +The following use case has integrated the [ArUco marker pipeline](../../user_guide/aruco_marker_pipeline/introduction.md) to map pilot gaze onto many cockpit instruments in real-time and then enable AOI fixation matching with the [gaze analysis pipeline](../../user_guide/gaze_analysis_pipeline/introduction.md). + +## Background + +The [HAIKU project](https://haikuproject.eu/) aims to pave the way for human-centric intelligent assistants in the aviation domain by supporting, among others, the pilot during startle or surprise events. +One of the features provided by the assistant through **ArGaze** is a situation awareness support that ensures the pilot updates his awareness of the aircraft state by monitoring his gaze and flight parameters. +When this support is active, relevant information is highlighted on the Primary Flight Display (PFD) and the Electronic Centralized Aircraft Monitor (ECAM). + + + +## Environment + +Due to the complexity of the cockpit simulator's geometry, pilot's eyes are tracked with a head-mounted eye tracker (Tobii Pro Glasses 2). +The gaze and scene camera video were captured through the Tobii SDK and processed in real-time on an NVIDIA Jetson Xavier computer. +ArUco markers were placed at various locations within the cockpit simulator to ensure that several of them were constantly visible in the field of view of the eye tracker camera. + + + +The [ArUco marker pipeline](../../user_guide/aruco_marker_pipeline/introduction.md) has enabled real-time gaze mapping onto multiple screens and panels around pilot-in-command position while [gaze analysis pipeline](../../user_guide/gaze_analysis_pipeline/introduction.md) was identifying fixations and matching them with dynamic AOIs related to each instruments. +To identify the relevant AOIs, a 3D model of the cockpit describing the AOI and the position of the markers has been realized. + + + +Finally, fixation events were sent in real-time through [Ivy bus middleware](https://gitlab.com/ivybus/ivy-python/) to the situation awareness software in charge of displaying attention getter onto the PFD screen. + +## Setup + +The setup to integrate **ArGaze** to the experiment is defined by 3 main files detailled in the next chapters: + +* The context file that captures gaze data and scene camera video: [live_streaming_context.json](context.md) +* The pipeline file that processes gaze data and scene camera video: [live_processing_pipeline.json](pipeline.md) +* The observers file that send fixation events via Ivy bus middleware: [observers.py](observers.md) + +As any **ArGaze** setup, it is loaded by executing the [*load* command](../../user_guide/utils/main_commands.md): + +```shell +python -m argaze load live_streaming_context.json +``` + +This command opens a GUI window that allows to start gaze calibration, to launch recording and to monitor gaze mapping. Another window is also opened to display gaze mapping onto PFD screen. + + |