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Proceedings Paper

Infrared animal modeling for training ATR algorithms
Author(s): Tommy Johansson; Jan Fagerström; Mikael Karlsson; Anna Linderhed; Andreas Persson
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Paper Abstract

There are very good automatic detection algorithms available to be used in an Automatic Target Recognition applications. However they need lots of data for training the detector for the specific use, e.g., performing an inventory of wild animals. Ongoing work use thermally correct infrared models of animals for training the detector because collecting real images from these wild animals is too expensive if even possible. This paper describes the process of designing a good IR model of the animals, and the validation process of the thermal model. Several animals are modeled using RadThermIR to be used for training detection algorithms. Animal models are based on commercially available CAD models and are initiated by temperature values from real IR measurements in several different weather conditions. The modeling extends the available set of training images by introducing different weather conditions and different poses of the animal. Fat and fur thickness of the animal is modeled with respect to climate and weather.

Paper Details

Date Published: 26 October 2010
PDF: 8 pages
Proc. SPIE 7833, Unmanned/Unattended Sensors and Sensor Networks VII, 783303 (26 October 2010); doi: 10.1117/12.865219
Show Author Affiliations
Tommy Johansson, Swedish Defence Research Agency (Sweden)
Jan Fagerström, Swedish Defence Research Agency (Sweden)
Mikael Karlsson, Swedish Defence Research Agency (Sweden)
Anna Linderhed, Swedish Defence Research Agency (Sweden)
Andreas Persson, Swedish Defence Research Agency (Sweden)


Published in SPIE Proceedings Vol. 7833:
Unmanned/Unattended Sensors and Sensor Networks VII
Edward M. Carapezza, Editor(s)

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