Samurai monitors us

 StartUpMeetingSAMURAI Suspicious and Abnormal behaviour Monitoring Using a netwoRk of cAmeras for sItuation awareness enhancement

 StartUpMeetingSAMURAI Suspicious and Abnormal behaviour Monitoring Using a netwoRk of cAmeras for sItuation awareness enhancement

SAMURAI is a collaborative project funded under the European Commission Seventh Framework Programme Theme 10 (Security). The aim of SAMURAI is to develop and integrate an innovative intelligent surveillance system for monitoring people and vehicle activities at both inside and surrounding areas of a critical public infrastructure.

The project consortium consists of 8 partners across the EU, led by Queen Mary, University of London with Professor Shaogang Gong as the project co-ordinator.

Beneficiary Name

Acroynm

Country

Co-Ordinator

Queen Mary University of London:
Department of Computer Science
Computer Vision Group

QMUL

UK (United Kingdom)

Prof Shaogang Gong

Università di Verona:
Department Computer Science
Vision, Image Processing & Sound – VIPS lab

UNIVR

IT (Italy)

Prof Vittorio Murino

Elsag Datamat S.p.A.

ED

IT (Italy)

Giovanni Garibotto

Waterfall Solutions Ltd.

WS

UK (United Kingdom)

Dr Duncan Hickman

Borthwick-Pignon OÛ

BPS

EE (Estonia)

Leon Borthwick

Esaprojekt SP. Z. O.O.

ESA

PL (Poland)

Katarzyna Ptasznik

Syndicat Mixte des Transports pour le Rhône et l’Agglomération Lyonnaise

SYTRAL

FR (France)

Michel Rodet

BAA Limited

BAA

UK (United Kingdom)

Huw Farmer

 

Project Aims

The aim of SAMURAI is to develop and integrate an innovative intelligent surveillance system for robust monitoring of both inside and surrounding areas of a critical public infrastructure. SAMURAI has three significant novelties that make it distinctive from other recent and ongoing relevant activities both in the EU and elsewhere: *SAMURAI is to employ networked heterogeneous sensors rather than CCTV cameras alone so that multiple complementary sources of information can be fused to create a visualisation of a more complete 'big picture’ of a crowded public space. * Existing systems focus on analysing recorded video using pre-defined hard rules, suffering from unaccepted false alarms. SAMURAI is to develop a real-time adaptive behaviour profiling and abnormality detection system for alarm event alert and prediction with much reduced false operators and mobile sensory input for patrolling security staff for a hybrid context-aware based abnormal behaviour recognition. This is in contrary to current video behaviour recognition systems that rely purely on information extracted from the video data, often too ambiguous to be effective.

SAMURAI has the following scientific objectives :

  • Develop innovative tools and systems for people, vehicle and luggage detection, tracking, type categorisation across a network of cameras under real world conditions.
  • Develop an abnormal detection system based on a heterogeneous sensor network consisting of both fix-positioned CCTV cameras and mobile wearable cameras with audio and positioning sensors. These networked heterogeneous sensors will function cooperatively to provide enhanced situation awareness.
  • Develop innovative tools using multi-modal data fusion and visualisation of heterogeneous sensor input to enable more effective control room operator queries.

The Team

Prof Sean Gong ………… Project Co-Ordinator …………

Dr Tony Xiang………… Assistant Project Co-Ordinator …………

Catherine Edlin………… Project Administrator …………

Adam Smith

BAA Limited

Alan Gunn

BAA Limited

Alberto Bianchi

Elsag Datamat

Andrea Fusiello

University of Verona

Ben James

Waterfall Solutions

Bogusław Legierski

Esaprojekt

Bob Koger

BPS

Catherine Edlin

Queen Mary University of London

Caroline Wardle

Queen Mary University of London

Dean Pignon

BPS

Duncan Hickman

Waterfall Solutions

Franco Selvaggi

Elsag Datamat

Giovanni Garibotto

Elsag Datamat

Gisella Corbellini

Elsag Datamat

Huw Farmer

BAA Limited

Weishi Zheng

Queen Mary University of London

Leon Borthwick

BPS

Leonardo Roncarolo

Elsag Datamat

Marco Cristani

University of Verona

Michela Farenzena

University of Verona

Maciej Kotok

Esaprojekt

Moira Smith

Waterfall Solutions

Eve-Marie Moos

SYTRAL

Paul Pignon

BPS

Piotr Góral

Esaprojekt

Rafal Dunal

Esaprojekt

Michel Rodet

SYTRAL

Scott Page

Waterfall Solutions

Sean Gong

Queen Mary University of London

Stephen Challis

BAA Limited

Timothy Hospedales

Queen Mary University of London

Tony Xiang

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