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Person detection in LWIR imagery using image retrieval
Author(s) -
Thomas Müller,
Daniel Manger
Publication year - 2013
Publication title -
proceedings of spie, the international society for optical engineering/proceedings of spie
Language(s) - English
Resource type - Conference proceedings
SCImago Journal Rank - 0.192
H-Index - 176
eISSN - 1996-756X
pISSN - 0277-786X
DOI - 10.1117/12.2015853
Subject(s) - computer science , robustness (evolution) , artificial intelligence , computer vision , situation awareness , image retrieval , object detection , image (mathematics) , image processing , remote sensing , pattern recognition (psychology) , biochemistry , chemistry , geology , engineering , gene , aerospace engineering
This paper addresses the detection and localization of persons in LWIR imagery which is useful especially in visual surveillance tasks such as intruder detection in military camps or for gaining situational awareness. A robust image retrieval function is used after a previous hot spot detection and localization step in LWIR using a suitable, extensive image data base that covers a variety of different shapes and appearances of persons in LWIR. The basic idea behind this approach is, in contrast to the visual optical band (VIS), that persons in thermal infrared exhibit somehow similar, weakly individualized signatures which can be matched to a sufficient degree to images in the data base and, thus, can be distinguished from background structures and other objects. Dedicated pre and post processing routines optimize the results and compensate for a possibly occuring lack of image features needed by the image retrieval function. The achieved results document the practical benefit and the robustness of the presented aproach

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