Working on gaze analysis pipeline documentation. Still in progress...

1 files changed, 21 insertions, 5 deletions

diff --git a/docs/index.md b/docs/index.md
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 title: What is ArGaze?
 ---
 
-# Enable gaze tracking in AR environment
+# Enable modular gaze processing pipeline
 
 **Useful links**: [Installation](installation) | [Source Repository](https://git.recherche.enac.fr/projects/argaze/repository) | [Issue Tracker](https://git.recherche.enac.fr/projects/argaze/issues) | [Contact](mailto:achil-contact@recherche.enac.fr)
 
-**ArGaze** python toolkit provides solutions to build 3D modeled **Augmented Reality (AR)** environment defining **Areas Of Interest (AOI)** mapped on <a href="https://docs.opencv.org/4.x/d5/dae/tutorial_aruco_detection.html" target="_blank">OpenCV ArUco markers</a> and so ease experimentation design with wearable eye tracker device.
+**ArGaze** python toolkit provides a set of classes to build custom-made gaze processing pipelines that works with any kind of eye tracker devices.
 
-Further, tracked gaze can be projected onto AR environment for live or post **gaze analysis** thanks to **timestamped data** features.
+![AGaze pipeline](img/argaze_pipeline.png)
+
+## Gaze analysis pipeline
+
+Whether in real time or in post-processing, **ArGaze** provides extensible plugins library allowing to select application specific algorithm at each pipeline step:  
+
+* **Fixation/Saccade identification**: dispersion threshold identification, velocity threshold identification, ...  
+* **Area Of Interest (AOI) matching**: fixation deviation circle matching, ...
+* **Scan path analysis**: transition matrix, entropy, exploit/explore ratio, ...
+
+Once incoming data formatted as required, all those gaze analysis features can be used with any screen-based eye tracker devices.
+
+[Learn how to build gaze analysis pipelines for various use cases by reading user guide dedicated section](./user_guide/gaze_analysis_pipeline/introduction).
+
+## Augmented reality pipeline
+
+Things goes harder when gaze data comes from head-mounted eye tracker devices. That's why **ArGaze** enable 3D modeled **Augmented Reality (AR)** environment description including **Areas Of Interest (AOI)** mapped on <a href="https://docs.opencv.org/4.x/d5/dae/tutorial_aruco_detection.html" target="_blank">OpenCV ArUco markers</a>.
 
 ![AR environment axis](img/ar_environment_axis.png)
 
-ArGaze can be combined with any wearable eye tracking device python library like Tobii or Pupil glasses.
+This AR pipeline can be combined with any wearable eye tracking device python library like Tobii or Pupill glasses.
 
 !!! note
    
-      *This work is greatly inspired by [Andrew T. Duchowski, Vsevolod Peysakhovich and Krzysztof Krejtz article](https://git.recherche.enac.fr/attachments/download/1990/Using_Pose_Estimation_to_Map_Gaze_to_Detected_Fidu.pdf) about using pose estimation to map gaze to detected fiducial markers.*
+      *AR pipeline is greatly inspired by [Andrew T. Duchowski, Vsevolod Peysakhovich and Krzysztof Krejtz article](https://git.recherche.enac.fr/attachments/download/1990/Using_Pose_Estimation_to_Map_Gaze_to_Detected_Fidu.pdf) about using pose estimation to map gaze to detected fiducial markers.*