Detection and tracking of people with sudden changes in motion using two-layered laser range sensors

Abstract

This paper presents a people tracking system with multiple sensor nodes allocated in an environment. Each sensor node consists of a two-layered laser range sensor (LRS) that detects the positions of heads and knees of people. From the laser images of the people, heuristic-rule-based and global-nearest- neighbor (GNN)-based data association can identify a large number of people in crowded environments. The identified people are tracked via a model-based tracker; the interacting multiple model (IMM) estimator is applied to track people suddenly changing in motion, such as walking, running, going/stopping suddenly, and turning suddenly. Simulation and experimental results validate our people tracking method. © 2012 The Japan Society of Mechanical Engineers.