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Vision-based drone flight control and crowd or riot analysis with efficient color histogram based tracking

: Müller, Thomas; Müller, Markus

Volltext urn:nbn:de:0011-n-1924342 (862 KByte PDF)
MD5 Fingerprint: 19818d9fa10bc7986133ec14df0c7f14
Copyright 2011 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.
Erstellt am: 7.7.2012

Henry, D.J. ; Society of Photo-Optical Instrumentation Engineers -SPIE-, Bellingham/Wash.; Society for Imaging Science and Technology -IS&T-:
Airborne intelligence, surveillance, reconnaissance (ISR) systems and applications VIII : 27 - 28 April 2011, Orlando, Florida, United States
Bellingham, WA: SPIE, 2011 (Proceedings of SPIE 8020)
ISBN: 978-0-8194-8594-6
Paper 80200R
Airborne Intelligence, Surveillance, Reconnaissance (ISR) Systems and Applications Conference <8, 2011, Orlando/Fla.>
Konferenzbeitrag, Elektronische Publikation
Fraunhofer IOSB ()
highly efficient object tracking; color histogram; color finger print; unmanned aerial vehicles (UAV); automatic visual closed-loop control; crowd evaluation

Object tracking is a direct or indirect key issue in many different military applications like visual surveillance, automatic visual closed-loop control of UAVs (unmanned aerial vehicles) and PTZ-cameras, or in the field of crowd evaluations in order to detect or analyse a riot emergence. Of course, a high robustness is the most important feature of the underlying tracker, but this is hindered significantly the more the tracker needs to have low calculation times. In the UAV application introduced in this paper the tracker has to be extraordinarily quick. In order to optimize the calculation time and the robustness in combination as far as possible, a highly efficient tracking procedure is presented for the above mentioned application fields which relies on well-known color histograms but uses them in a novel manner. This procedure bases on the calculation of a color weighting vector representing the significances of object colors like a kind of an object's color finger print. Several examples from the above mentioned military applications are shown to demonstrate the practical relevance and the performance of the presented tracking approach.