A laser-based people tracker

Describes a method for real-time tracking of people in everyday environments, using multiple planar laser range-finders. People tracking is a well-studied problem in machine vision; we adapt some of those methods to laser range-finders. We group range measurements into entities such as blobs and objects, and use a Kalman filter to estimate trajectories for these objects. The filter is able to generate smooth trajectories, even when objects are occluded. The paper presents our evaluation of the tracker´s performance in a series of four experiments