5 October 2017 Person detection and tracking with a 360° lidar system
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Proceedings Volume 10434, Electro-Optical Remote Sensing XI; 104340L (2017); doi: 10.1117/12.2278215
Event: SPIE Security + Defence, 2017, Warsaw, Poland
Abstract
Today it is easily possible to generate dense point clouds of the sensor environment using 360° LiDAR (Light Detection and Ranging) sensors which are available since a number of years. The interpretation of these data is much more challenging. For the automated data evaluation the detection and classification of objects is a fundamental task. Especially in urban scenarios moving objects like persons or vehicles are of particular interest, for instance in automatic collision avoidance, for mobile sensor platforms or surveillance tasks.

In literature there are several approaches for automated person detection in point clouds. While most techniques show acceptable results in object detection, the computation time is often crucial. The runtime can be problematic, especially due to the amount of data in the panoramic 360° point clouds. On the other hand, for most applications an object detection and classification in real time is needed.

The paper presents a proposal for a fast, real-time capable algorithm for person detection, classification and tracking in panoramic point clouds.
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Marcus Hammer, Marcus Hebel, Michael Arens, "Person detection and tracking with a 360° lidar system", Proc. SPIE 10434, Electro-Optical Remote Sensing XI, 104340L (5 October 2017); doi: 10.1117/12.2278215; http://dx.doi.org/10.1117/12.2278215
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KEYWORDS
Clouds

LIDAR

Sensors

Detection and tracking algorithms

3D modeling

Panoramic photography

Environmental sensing

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