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Author | Yainuvis Socarras; Sebastian Ramos; David Vazquez; Antonio Lopez; Theo Gevers | ||||
Title | Adapting Pedestrian Detection from Synthetic to Far Infrared Images | Type | Conference Article | ||
Year | 2013 | Publication | ICCV Workshop on Visual Domain Adaptation and Dataset Bias | Abbreviated Journal | |
Volume | Issue | Pages | |||
Keywords | Domain Adaptation; Far Infrared; Pedestrian Detection | ||||
Abstract | We present different techniques to adapt a pedestrian classifier trained with synthetic images and the corresponding automatically generated annotations to operate with far infrared (FIR) images. The information contained in this kind of images allow us to develop a robust pedestrian detector invariant to extreme illumination changes. | ||||
Address | Sydney; Australia; December 2013 | ||||
Corporate Author | Thesis | ||||
Publisher | Place of Publication | Sydney, Australy | Editor | ||
Language | English | Summary Language | Original Title | ||
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | ISBN | Medium | |||
Area | Expedition | Conference | ICCVW-VisDA | ||
Notes | ADAS; 600.054; 600.055; 600.057; 601.217;ISE | Approved | no | ||
Call Number | ADAS @ adas @ SRV2013 | Serial | 2334 | ||
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