Vision-Based Human Posture Detection from a Virtual Home-Care Unmanned Aerial Vehicle
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Autores: Andrés Bustamante Londoño, Lidia María Belmonte, Antonio Pereira González, Pascual González Galindo, Antonio Fernández Caballero
, Rafael Morales Ruiz
- Localización: Bio-inspired Systems and Applications: from Robotics to Ambient Intelligence: 9th International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2022, Puerto de la Cruz, Tenerife, Spain, May 31 – June 3, 2022, Proceedings, Part II / José Manuel Ferrández Vicente (dir. congr.) , José Ramón Álvarez Sánchez (dir. congr.) , Félix de la Paz López (dir. congr.) , Hojjat Adeli (aut.), 2022, ISBN 978-3-031-06527-9, págs. 482-491
- Idioma: inglés
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Resumen
Monitoring is essential to provide assistance to people who require home care due to their age or health condition. This paper presents the vision-based detection of three postures of a person (standing, sitting and laying down) from an unmanned aerial vehicle. The proposal uses the MediaPipe Pose Python module, considering only seven skeleton points and a set of trigonometric calculations. The work is evaluated in a Unity virtual reality (VR) environment that simulates the monitoring process of an assistant UAV. The images acquired by the UAV’s on-board camera are sent from the VR visualiser to the Python module via the Message Queue Telemetry Transport (MQTT) protocol. The simulation shows very promising results for the detection of a person’s postures.
