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  4. Learning transmodal person detectors from single spectral training sets
 
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2013
Conference Paper
Title

Learning transmodal person detectors from single spectral training sets

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.
Author(s)
Kieritz, Hilke
Hübner, Wolfgang  
Arens, Michael  
Mainwork
Optics and Photonics for Counterterrorism, Crime Fighting and Defence IX  
Conference
Conference "Optics and Photonics for Counterterrorism, Crime Fighting and Defence" 2013  
Conference "Optical Materials and Biomaterials in Security and Defence Systems Technology" 2013  
DOI
10.1117/12.2028651
Language
English
Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung IOSB  
Keyword(s)
  • person detection

  • infrared

  • visible

  • transmodal detection

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