Multisensor benchmark data for riot control

Uwe Jäger; Marc Höpken; Bernhard Dürr; Jürgen Metzler; Dieter Willersinn

doi:10.1117/12.799822

7 October 2008 Multisensor benchmark data for riot control

Uwe Jäger, Marc Höpken, Bernhard Dürr, Jürgen Metzler, Dieter Willersinn

Proceedings Volume 7114, Electro-Optical Remote Sensing, Photonic Technologies, and Applications II; 711403 (2008) https://doi.org/10.1117/12.799822
Event: SPIE Security + Defence, 2008, Cardiff, Wales, United Kingdom

Abstract

Quick and precise response is essential for riot squads when coping with escalating violence in crowds. Often it is just a single person, known as the leader of the gang, who instigates other people and thus is responsible of excesses. Putting this single person out of action in most cases leads to a de-escalating situation. Fostering de-escalations is one of the main tasks of crowd and riot control. To do so, extensive situation awareness is mandatory for the squads and can be promoted by technical means such as video surveillance using sensor networks. To develop software tools for situation awareness appropriate input data with well-known quality is needed. Furthermore, the developer must be able to measure algorithm performance and ongoing improvements. Last but not least, after algorithm development has finished and marketing aspects emerge, meeting of specifications must be proved. This paper describes a multisensor benchmark which exactly serves this purpose. We first define the underlying algorithm task. Then we explain details about data acquisition and sensor setup and finally we give some insight into quality measures of multisensor data. Currently, the multisensor benchmark described in this paper is applied to the development of basic algorithms for situational awareness, e.g. tracking of individuals in a crowd.

Citation Download Citation

Uwe Jäger, Marc Höpken, Bernhard Dürr, Jürgen Metzler, and Dieter Willersinn "Multisensor benchmark data for riot control", Proc. SPIE 7114, Electro-Optical Remote Sensing, Photonic Technologies, and Applications II, 711403 (7 October 2008); https://doi.org/10.1117/12.799822

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

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
5 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Sensors

Detection and tracking algorithms

Software development

Video

Algorithm development

Data acquisition

Video surveillance

Show All Keywords

Keywords/Phrases

Search In:

Publication Years