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

Thomas Müller; Markus Müller

doi:10.1117/12.884213

25 May 2011 Vision-based drone flight control and crowd or riot analysis with efficient color histogram based tracking

Thomas Müller, Markus Müller

Proceedings Volume 8020, Airborne Intelligence, Surveillance, Reconnaissance (ISR) Systems and Applications VIII; 80200R (2011) https://doi.org/10.1117/12.884213
Event: SPIE Defense, Security, and Sensing, 2011, Orlando, Florida, United States

Abstract

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.

Citation Download Citation

Thomas Müller and Markus Müller "Vision-based drone flight control and crowd or riot analysis with efficient color histogram based tracking", Proc. SPIE 8020, Airborne Intelligence, Surveillance, Reconnaissance (ISR) Systems and Applications VIII, 80200R (25 May 2011); https://doi.org/10.1117/12.884213

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available