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Hot spot detection and classification in LWIR videos for person recognition

 
: Teutsch, M.; Müller, Thomas

:
Fulltext urn:nbn:de:0011-n-2644394 (431 KByte PDF)
MD5 Fingerprint: 500ca31209cf375274d198c0a66ae4c3
Copyright Society of Photo-Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.
Created on: 17.4.2014


Sadjadi, F.A. ; Society of Photo-Optical Instrumentation Engineers -SPIE-, Bellingham/Wash.:
Automatic target recognition XXIII : 29 - 30 April 2013, Baltimore, Maryland, United States
Bellingham, WA: SPIE, 2013 (Proceedings of SPIE 8744)
ISBN: 978-0-8194-9535-8
Paper 87440F
Conference "Automatic Target Recognition" <23, 2013, Baltimore/Md.>
English
Conference Paper, Electronic Publication
Fraunhofer IOSB ()
thermal infrared; IR; MWIR and LWIR; warm area localization; human detection; person classification; visual surveillance; intruder recognition; temporal context

Abstract
Person recognition is a key issue in visual surveillance. It is needed in many security applications such as intruder detection in military camps but also for gaining situational awareness in a variety of different safety applications. A solution for LWIR videos coming from a moving camera is presented that is based on hot spot classification to distinguish persons from background clutter and other objects. We especially consider objects in higher distance with small appearance in the image. Hot spots are detected and tracked along the videos. Various image features are extracted from the spots and different classifiers such as SVM or AdaBoost are evaluated and extended to utilize the temporal information. We demonstrate that taking advantage of this temporal context can improve the classification performance.

: http://publica.fraunhofer.de/documents/N-264439.html