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Rita Cucchiara, Università di Modena e Reggio Emilia,

Videosorveglianza : la ricerca in Visione Artificiale per il riconoscimento automatico di persone ed eventi . VIDEOSORVEGLIANZA Profili sociologici, criminologici, culturali e giuridici nell’ottica smart city Milano 24 Maggio, Università Cattolica del Sacro Cuore.

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Rita Cucchiara, Università di Modena e Reggio Emilia,

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  1. Videosorveglianza: la ricerca in Visione Artificiale per il riconoscimento automatico di persone ed eventi VIDEOSORVEGLIANZA Profili sociologici, criminologici, culturali e giuridici nell’ottica smart city Milano 24 Maggio, Università Cattolica del Sacro Cuore Prof. Rita Cucchiara, Università di Modena e Reggio Emilia, Direttore del centro Softech ICT http://www.Imagelab.ing.unimore.it Rita Cucchiara, Università di Modena e Reggio Emilia,

  2. Welcome in Modena • The Second Short Spring School in Surveillance • is organized by • -University of Modena and Reggio Emilia • -Softech-ICT Interdip. Research Center in ICT • -Dipartimento di Ingegneria Enzo Ferrari • - ImageLab • Co-Sponsored by • - FondazioneCassa di Risparmio di Modena • - GIRPR (Italian chapter of IAPR)

  3. UNIMORE: Where we are… Università di Modena e Reggio Emilia Emilia Romagna, Italia Dipartimento di Ingegneria “Enzo Ferrari” ImageLab

  4. WHY S5? • A research School in • (computer vision and pattern recognition for) • Video Surveillance. • Mainly a school for researchers • few hot selected topics • Short (but intensive) school in Spring period • A Second edition…

  5. S4 the 2011 edition Multicamera & applications Tracking Security and Forensics Face and expression Architecture and systems Large Crowd

  6. Again Surveillance… Why another (short spring) School in surveillance? Surveillance Surely is an industrial gold filed … is it still an open research problem?

  7. The market • The global Intelligent Video Surveillance (IVS) & Video Analytics (VA) industry revenues* • totaled $13.5 billion in 2012, • and are estimated to reach $39 billion in 2020. • The rapid market growth is driven by the following dynamics: • Increased use of video surveillance. • Migration from analog to digital cameras and to IP based cameras. • Technology maturity. Video analytics algorithms, processors, applications and products underwent a decade of technological evolution to intelligent video processing, based on advancements in image processing, enabling automatic detection of signatures detection and identification. • Cost reduction of video analytic systems. Driven by the falling prices of image processing DSPs and communication systems. Cost-performance of new edge-based video analytics DSP technologies (e.g., Intel, Texas Instruments DSPs). From the "Intelligent Video Surveillance, VCA & Video Analytics: Technologies & Global Market – 2013-2020"

  8. The market • Human operators entail high cost & high rate of overlooked events. • Real time analysis of video images and recorded footage is a need that can hardly be answered effectively by human operators, and manpower cost. Furthermore, human operators fatigue and boredom cause a high rate of overlooked events. • It takes IVS, VCA and VA to process trillions of video surveillance-hours generated annually. • By 2011 over 165 million video surveillance cameras installed worldwide captured 1.4 trillion video-hours. • the investing growth of 9-11% year , captured video surveillance will reach approximately 3.3 Trillion video-hours in 2020. • A hypothetical analysis assuming that 20% of the most critical video stream should have been reviewed by human operators, results in a (hypothetical) need to employ (by 2011) a workforce of over 100 million operators (working 8 hours daily, 300 days a year). • Intelligent video surveillance and video analytics with mature technology have attracted a lot of attention. ---the global market* will triple by 2020.

  9. THE RESEARCH • 1998 the first workshop on AVSS (advanced video-based surveillance system) in Genoa • 2000 The first IEEE Transaction PAMI Special issue on video surveillance • 2003 the first IEEE conference AVSS • ….. FIFTTEEN YEARS OF RESEARCH

  10. Some statistics • “Video Surveillance” : Google scholar 54000 items, • IEEEXplore 6407 items • from IEEEXplore papers with “video surveillance” keyword

  11. statistics • IEEE conference papers with video surveillance and ……

  12. statistics • IEEE journal papers with video surveillance and ……

  13. surveillance • 1) A growing interest in PEOPLE surveillance • 2) From SECURITY • to SOCIAL and WELLBEING • 3) A research interest in computer vision AND learning

  14. VideOSurveillance Single camera  Multiple cameras Acquisition Detection Moving object detection Single object/people  Multiple targets, cluttered, occluded.. Tracking • Linear prediction • Generative models • Stocasticprediction 2000 Research Understanding Purposive

  15. PEOPLESurveillancein the new decade Acquisition Detection & Tracking SPATIO-TEMPORAL REASONING Learning & Inferring BIG DATA ANALYSIS Searching & Recognizing 2010 Research HUMAN FEEDBACK

  16. People Analysis IS PERVASIVE • From Security • Surveillance: Real time detection, Border, Zone control, Activity monitoring, Traffic, urban control… • Safety: traffic-automotive control; crowd monitoring, home, working area control • Forensics: Video Mining, Identity assessment, Likelihood ratio support • To Multimedia Video analysis, broadcasting analysis, Digital Library annotation, Sport action recognition, Human Interaction, Gaming • To (Social) Wellbeing Retail analysis, Comfort in architecture Design, Building Automation, Healthcare, Entertainment, Graphics..

  17. People ANALYSIS • Many applications.. Same problem: •  detect people, their identity and behavior

  18. People surveillance: what at IMAGELAB • Detection &Tracking • People (and crowd) Detectionand Tracking • With multisensory data • Learning& inferring • People Identification and (Ri-)Identification • Search & Recognition • People Searchby similarity A-priori Models Visual Learning

  19. Surveillance at S5 • The topics: Ci pensoioquandoavro’ gli abstract

  20. SURVEILLANCE aT S5 • The lecturers: • Arnold Smeulders CWI Amsterdam, the Netherlands  • Bernhard Rinner Alpen-Adria-Universität Klagenfurt, Austria • Francois Bremond INRIA, France  • Greg Mori Simon Fraser University, Canada 

  21. SURVEILLANCE aT S5 • The lecturers: • Horst Bischof Institute for Computer Graphics and Vision, Inffeldgasse Graz, Austria  • Larry Davis Institute for Advanced Computer Studies, Univ. of Maryland, USA  • Shmuel Peleg The Hebrew University of Jerusalem, Israel 

  22. SURVEILLANCE aT S5 • The attendees

  23. THANKS.. Prof. Rita Cucchiara Dipartimento di Ingegneria Enzo Ferrari Res. Center SOFTECH-ICT Università degli Studi di Modena e Reggio Emilia Rita.cucchiara@unimore.it • Imagelab Andrea Prati [IUAV-Venezia] • Costantino Grana • Roberto Vezzani • Simone Calderara • Giovanni Gualdi , Paolo Piccinini, Daniele Borghesani, AdnanRashid, Paolo Santinelli • Davide Baltieri , Dalia Coppi, Michele Fornaciari ,Marco Manfredi • VISION-E srl • Rudy Melli, Giuliano Pistoni, Emanuele Perini http://imagelab.ing.unimo.it

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