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Proceedings Paper

Learning transmodal person detectors from single spectral training sets
Author(s): Hilke Kieritz; Wolfgang Hübner; Michael Arens
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Paper 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.

Paper Details

Date Published: 16 October 2013
PDF: 9 pages
Proc. SPIE 8901, Optics and Photonics for Counterterrorism, Crime Fighting and Defence IX; and Optical Materials and Biomaterials in Security and Defence Systems Technology X, 89010F (16 October 2013); doi: 10.1117/12.2028651
Show Author Affiliations
Hilke Kieritz, Fraunhofer Institute for Optronics, System Technologies, and Image Exploitation (Germany)
Wolfgang Hübner, Fraunhofer Institute for Optronics, System Technologies, and Image Exploitation (Germany)
Michael Arens, Fraunhofer Institute for Optronics, System Technologies, and Image Exploitation (Germany)


Published in SPIE Proceedings Vol. 8901:
Optics and Photonics for Counterterrorism, Crime Fighting and Defence IX; and Optical Materials and Biomaterials in Security and Defence Systems Technology X
Roberto Zamboni; Douglas Burgess; Gari Owen; Francois Kajzar; Attila A. Szep, Editor(s)

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