Infrared animal modeling for training ATR algorithms

Tommy Johansson; Jan Fagerström; Mikael Karlsson; Anna Linderhed; Andreas Persson

doi:10.1117/12.865219

26 October 2010 Infrared animal modeling for training ATR algorithms

Tommy Johansson, Jan Fagerström, Mikael Karlsson, Anna Linderhed, Andreas Persson

Proceedings Volume 7833, Unmanned/Unattended Sensors and Sensor Networks VII; 783303 (2010) https://doi.org/10.1117/12.865219
Event: SPIE Security + Defence, 2010, Toulouse, France

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.

Citation Download Citation

Tommy Johansson, Jan Fagerström, Mikael Karlsson, Anna Linderhed, and Andreas Persson "Infrared animal modeling for training ATR algorithms", Proc. SPIE 7833, Unmanned/Unattended Sensors and Sensor Networks VII, 783303 (26 October 2010); https://doi.org/10.1117/12.865219

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