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@@ -1,13 +1,17 @@ -# 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) + +{ 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.* |