3D Object-Camera and 3D Face-Camera Pose Estimation for Quadcopter Control: Application to Remote Labs

Fawzi Khattar (1) , Fadi Dornaika (1) , Benoît Larroque (2) , Franck Luthon (1)

1 LIUPPA - Laboratoire Informatique de l'Université de Pau et des Pays de l'Adour
2 SIAME - Laboratoire des Sciences de l'Ingénieur Appliquées à la Mécanique et au génie Electrique

We present the implementation of two visual pose estimation algorithms (object-camera and face-camera) with a control system for a low cost quadcopter for an application in a remote electronic laboratory. The objective is threefold: (i) to allow the drone to inspect instruments in the remote lab, (ii) to localize a teacher and center his face in the image for student-teacher remote communication, (iii) and to return back home and land on a platform for automatic recharge of the batteries. The object-camera localization system is composed of two complementary visual approaches: (i) a visual SLAM (Simultaneous Localization And Mapping) system, and (ii) a homography-based localization system. We extend the application scenarios of the SLAM system by allowing close range inspection of a planar instrument and autonomous landing. The face-camera localization system is based on 3D modeling of the face, and a state of the art 2D facial point detector. Experiments conducted in a remote laboratory workspace are presented. They prove the robustness of the proposed object-camera visual pose system compared to the SLAM system, the performance of the face-camera visual servoing and pose estimation system in terms of real-time, robustness and accuracy.

Domaines: Automatique / Robotique; Vision par ordinateur et reconnaissance de formes [cs.CV]

Fawzi Khattar, Fadi Dornaika, Benoît Larroque, Franck Luthon. 3D Object-Camera and 3D Face-Camera Pose Estimation for Quadcopter Control: Application to Remote Labs. Advanced Concepts for Intelligent Vision Systems 19th International Conference, ACIVS 2018, Poitiers, France, September 24–27, 2018, Proceedings, 11182, pp.99-111, 2018, Lecture Notes in Computer Science, ⟨10.1007/978-3-030-01449-0_9⟩. ⟨hal-02192546⟩