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Learning transmodal person detectors from single spectral training sets

 
: Kieritz, Hilke; Hübner, Wolfgang; Arens, Michael

:

Burgess, D. ; Society of Photo-Optical Instrumentation Engineers -SPIE-, Bellingham/Wash.:
Optics and Photonics for Counterterrorism, Crime Fighting and Defence IX : And Optical Materials and Biomaterials in Security and Defence Systems Technology X; 23 - 24 September 2013, Dresden
Bellingham, WA: SPIE, 2013 (Proceedings of SPIE 8901)
ISBN: 978-0-8194-9770-3
Paper 89010F
Conference "Optics and Photonics for Counterterrorism, Crime Fighting and Defence" <9, 2013, Dresden>
Conference "Optical Materials and Biomaterials in Security and Defence Systems Technology" <10, 2013, Dresden>
English
Conference Paper
Fraunhofer IOSB ()
person detection; infrared; visible; transmodal detection

Abstract
Annotating data for training a person detector is a tedious procedure. Therefore it is worthwhile to use freely available datasets. When detecting in the infrared spectrum it is not obvious that person images from the visible spectrum can be used to train a detector operable in IR. We show that it is possible to train a transmodel detector, which can be used to detect in IR as well as in the visible spectrum. Therefor we use integral channel features in combination with boosting based feature selection, in order to analyze which features are effective for generating the effect of transmodality.

: http://publica.fraunhofer.de/documents/N-261248.html