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+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).
+
+![SA alert](../../img/haiku_sa_alert.png)
+
+## 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.
+
+![SimOne cockpit](../../img/simone_cockpit.png)
+
+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.
+
+![ArUco markers and AOI scene](../../img/haiku_aoi.png)
+
+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.
+
+![ArGaze load GUI for Haiku](../../img/argaze_load_gui_haiku.png)