The detection of objects, or persons, is a common task in the fields of environment surveillance, object observation or
danger defense. There are several approaches for automated detection with conventional imaging sensors as well as with
LiDAR sensors, but for the latter the real-time detection is hampered by the scanning character and therefore by the data
distortion of most LiDAR systems.
The paper presents a solution for real-time data acquisition of a flash LiDAR sensor with synchronous raw data analysis,
point cloud calculation, object detection, calculation of the next best view and steering of the pan-tilt head of the sensor.
As a result the attention is always focused on the object, independent of the behavior of the object. Even for highly
volatile and rapid changes in the direction of motion the object is kept in the field of view.
The experimental setup used in this paper is realized with an elementary person detection algorithm in medium distances
(20 m to 60 m) to show the efficiency of the system for objects with a high angular speed. It is easy to replace the
detection part by any other object detection algorithm and thus it is easy to track nearly any object, for example a car or a
boat or an UAV in various distances.
Marcus Hammer, Marcus Hebel, and Michael Arens, "Automated object detection and tracking with a flash LiDAR system," Proc. SPIE 9988, Electro-Optical Remote Sensing X, 998803 (Presented at SPIE Security + Defence: September 26, 2016; Published: 21 October 2016); https://doi.org/10.1117/12.2240640.
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