Working on documentation architecture.

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diff --git a/README.md b/README.md
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-# Welcome to ArGaze's documentation
+# ArGaze documentation
+
+**Useful links**: [Installation](getting_started#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)
+
+![Logo](logo-large.png){ width=640px }
 
 **ArGaze** is a python toolkit to deal with gaze tracking in **Augmented Reality (AR) environment**.
 
-The ArGaze toolkit provides solutions to build 3D modeled 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.
+The ArGaze toolkit provides solutions to build 3D modeled 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.
 
 Further, tracked gaze can be projected onto AR environment for live or post **gaze analysis** thanks to **timestamped data** features. 
 
 ArGaze can be combined with any wearable eye tracking device python library like Tobii or Pupil glasses.
 
-Check out the [installation](getting_started#installation) section to start.
-
-Check out the [Code reference](argaze) section to get deeper into library architecture.
+!!! note
+   
+      *This work is greatly inspired by [Andrew T. Duchowski, Vsevolod Peysakhovich and Krzysztof Krejtz article](https://git.recherche.enac.fr/attachments/download/1942/Using_Pose_Estimation_to_Map_Gaze_to_Detected_Fidu.pdf) about using pose estimation to map gaze to detected fiducial markers.*