Work

Low Level Detection and Tracking for Robust Following of a Single Person in Cluttered Environment

Year: 2024

Type: conference-paper

Abstract: To deploy mobile robots in spaces that they will share with humans, mobile robots should have social navigation methods. One important feature to design such methods is the ability to follow a moving person. In this paper, we present how we detect and track a moving person that our mobile robot is following. A low level detection of the moving person followed, to detect the person independently of their position and orientation with respect to the mobile robot, is combined with a sliding window approach to track the moving person. Some experimental results show the robustness of the method on real scenarios.

Source: International Conference on Control, Automation, Robotics and Vision (ICARCV)

DOI: 10.1109/icarcv63323.2024.10821585

Author: Olivier Aycard

Institutions: Institut polytechnique de Grenoble, GIPSA-Lab, Université Grenoble Alpes

Language: English

Topic: Video Surveillance and Tracking Methods

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

Funder: Agence Nationale de la Recherche

Award: IDEX UGA