2026-08-05T15:43:25Zhttps://repisalud.isciii.es/rest/oai/request

oai:repisalud.isciii.es:20.500.12105/179322024-02-10T20:02:31Zcom_20.500.12105_15322com_20.500.12105_2051col_20.500.12105_16927

00925njm 22002777a 4500 dc Garcia-Salguero, Mercedes author Gonzalez-Jimenez, Javier author Moreno, Francisco-Angel author 2019-11-13 Human-Robot interaction represents a cornerstone of mobile robotics, especially within the field of social robots. In this context, user localization becomes of crucial importance for the interaction. This work investigates the capabilities of wide field-of-view RGB cameras to estimate the 3D position and orientation (i.e., the pose) of a user in the environment. For that, we employ a social robot endowed with a fish-eye camera hosted in a tilting head and develop two complementary approaches: (1) a fast method relying on a single image that estimates the user pose from the detection of their feet and does not require either the robot or the user to remain static during the reconstruction; and (2) a method that takes some views of the scene while the camera is being tilted and does not need the feet to be visible. Due to the particular setup of the tilting camera, special equations for 3D reconstruction have been developed. In both approaches, a CNN-based skeleton detector (OpenPose) is employed to identify humans within the image. A set of experiments with real data validate our two proposed methods, yielding similar results than commercial RGB-D cameras while surpassing them in terms of coverage of the scene (wider FoV and longer range) and robustness to light conditions. 10.3390/s19224943 1424-8220 Sensors (Basel, Switzerland) http://hdl.handle.net/10668/14740 31766197 http://hdl.handle.net/20.500.12105/17932 3D computer vision OpenPose RGB-D cameras Camera pose calibration Human body pose estimation Human–robot interaction Human 3D Pose Estimation with a Tilting Camera for Social Mobile Robot Interaction.