Paper
17 August 2000 Advanced automatic target recognition for police helicopter missions
Christoph Stahl, Paul Schoppmann
Author Affiliations +
Abstract
The results of a case study about the application of an advanced method for automatic target recognition to infrared imagery taken from police helicopter missions are presented. The method consists of the following steps: preprocessing, classification, fusion, postprocessing and tracking, and combines the three paradigms image pyramids, neural networks and bayesian nets. The technology has been developed using a variety of different scenes typical for military aircraft missions. Infrared cameras have been in use for several years at the Bavarian police helicopter forces and are highly valuable for night missions. Several object classes like 'persons' or 'vehicles' are tested and the possible discrimination between persons and animals is shown. The analysis of complex scenes with hidden objects and clutter shows the potentials and limitations of automatic target recognition for real-world tasks. Several display concepts illustrate the achievable improvement of the situation awareness. The similarities and differences between various mission types concerning object variability, time constraints, consequences of false alarms, etc. are discussed. Typical police actions like searching for missing persons or runaway criminals illustrate the advantages of automatic target recognition. The results demonstrate the possible operational benefits for the helicopter crew. Future work will include performance evaluation issues and a system integration concept for the target platform.
© (2000) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Christoph Stahl and Paul Schoppmann "Advanced automatic target recognition for police helicopter missions", Proc. SPIE 4050, Automatic Target Recognition X, (17 August 2000); https://doi.org/10.1117/12.395573
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Cited by 6 scholarly publications.
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KEYWORDS
Automatic target recognition

Infrared radiation

Infrared imaging

Neural networks

Image fusion

Sensors

Buildings

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