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Kinect-based people detection and tracking from small-footprint ground robots

Armando Pesenti Gritti, Oscar Tarabini, Jérôme Guzzi, Gianni A. Di, Vincenzo Caglioti, Luca Maria Gambardella, Alessandro Giusti

发表年份
2014
引用次数
46

摘要

Small-footprint mobile ground robots, such as the popular Turtlebot and Kobuki platforms, are by necessity equipped with sensors which lie close to the ground. Reliably detecting and tracking people from this viewpoint is a challenging problem, whose solution is a key requirement for many applications involving sharing of common spaces and close human-robot interaction. We present a robust solution for cluttered indoor environments, using an inexpensive RGB-D sensor such as the Microsoft Kinect or Asus Xtion. Even in challenging scenarios with multiple people in view at once and occluding each other, our system solves the person detection problem significantly better than alternative approaches, reaching a precision, recall and F1-score of 0.85, 0.81 and 0.83, respectively. Evaluation datasets, a real-time ROS-enabled implementation and demonstration videos are provided as supplementary material.

关键词

RGB color modelRobotFootprintComputer scienceComputer visionArtificial intelligenceKey (lock)Mobile robotTracking (education)Human–computer interaction

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