Intelligent Multimedia Surveillance

Nowadays, intelligent video surveillance has become an essential tool of the greatest importance for several security-related applications. With the growth of installed cameras and the increasing complexity of required algorithms, in-house self-contained video surveillance systems become a chimera for most institutions and (small) companies. The paradigm of Video Surveillance as a Service (VSaaS) helps distributing not only storage space in the cloud (necessary for handling large amounts of video data), but also infrastructures and computational power. This chapter will briefly introduce the motivations and the main characteristics of a VSaaS system, providing a case study where research-lab computer vision algorithms are integrated in a VSaaS platform. The lessons learnt and some future directions on this topic will be also highlighted.

[1]  Christopher Slobogin,et al.  Privacy at Risk: The New Government Surveillance and the Fourth Amendment , 2007 .

[2]  Bradley Malin,et al.  Preserving privacy by de-identifying face images , 2005, IEEE Transactions on Knowledge and Data Engineering.

[3]  Wesley De Neve,et al.  Privacy Protection in Video Surveillance Systems Using Scalable Video Coding , 2009, 2009 Sixth IEEE International Conference on Advanced Video and Signal Based Surveillance.

[4]  Nicholas R. Fyfe,et al.  Closed circuit television and the city , 1998 .

[5]  P. Yip,et al.  Discrete Cosine Transform: Algorithms, Advantages, Applications , 1990 .

[6]  Ankur Chattopadhyay,et al.  PrivacyCam: a Privacy Preserving Camera Using uCLinux on the Blackfin DSP , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

[7]  Rama Chellappa,et al.  Discriminant analysis of principal components for face recognition , 1998, Proceedings Third IEEE International Conference on Automatic Face and Gesture Recognition.

[8]  Andrew B. Watson,et al.  Image Compression Using the Discrete Cosine Transform , 1994 .

[9]  Touradj Ebrahimi,et al.  A framework for the validation of privacy protection solutions in video surveillance , 2010, 2010 IEEE International Conference on Multimedia and Expo.

[10]  Roberto Cipolla,et al.  Face recognition from video , 2006 .

[11]  Sharath Pankanti,et al.  Blinkering Surveillance: Enabling Video Privacy through Computer Vision , 2004 .

[12]  Mubarak Shah,et al.  Floor Fields for Tracking in High Density Crowd Scenes , 2008, ECCV.

[13]  Fadi Dornaika,et al.  Fast and reliable active appearance model search for 3-D face tracking , 2004, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[14]  Mohan S. Kankanhalli,et al.  Adaptive Transformation for Robust Privacy Protection in Video Surveillance , 2012, Adv. Multim..

[15]  Wesley De Neve,et al.  Objective and Subjective Evaluation of Content-Based Privacy Protection of Face Images in Video Surveillance Systems Using JPEG XR , 2013 .

[16]  John Torpey.  Identifying Citizens: ID Cards as Surveillance , 2010 .

[17]  Sean P. Hier,et al.  Privacy pragmatism and streetscape video surveillance in Canada , 2011 .

[18]  V. Kshirsagar,et al.  Face recognition using Eigenfaces , 2011, 2011 3rd International Conference on Computer Research and Development.

[19]  K. Plataniotis,et al.  Privacy Protected Surveillance Using Secure Visual Object Coding , 2008, IEEE Transactions on Circuits and Systems for Video Technology.

[20]  Borko Furht,et al.  New approaches to encryption and steganography for digital videos , 2007, Multimedia Systems.

[21]  Hwann-Tzong Chen,et al.  Multi-object tracking using dynamical graph matching , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[22]  David Murakami Wood,et al.  The Growth of CCTV: a global perspective on the international diffusion of video surveillance in publicly accessible space , 2002 .

[23]  Marc Langheinrich,et al.  Privacy by Design - Principles of Privacy-Aware Ubiquitous Systems , 2001, UbiComp.

[24]  Christopher Slobogin.  Public Privacy: Surveillance of Public Places and the Right to Anonymity , 2007 .

[25]  Kentaro Toyama,et al.  Wallflower: principles and practice of background maintenance , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.

[26]  Lisa Graves.  The Right to Privacy in Light of Presidents' Programs: What Project MINARET's Admissions Reveal about Modern Surveillance of Americans , 2010 .

[27]  Mukaddim Pathan,et al.  Security, Privacy and Trust in Cloud Systems , 2013 .

[28]  Aleksandra Karimaa.  Efficient Video Surveillance: Performance Evaluation in Distributed Video Surveillance Systems , 2011 .

[29]  Tomas A. Lipinski,et al.  The Digital Person: Technology and Privacy in the Information Age , 2008 .

[30]  Mark Tunick,et al.  Privacy in Public Places: Do GPS and Video Surveillance Provide Plain Views? , 2009 .

[31]  Gary R. Bradski,et al.  Learning OpenCV - computer vision with the OpenCV library: software that sees , 2008 .

[32]  Noboru Babaguchi,et al.  Recoverable Privacy Protection for Video Content Distribution , 2009, EURASIP J. Inf. Secur..

[33]  Elizabeth D. Mynatt,et al.  Designing audio aura , 1998, CHI.

[34]  Augusto Sarti,et al.  Scream and gunshot detection and localization for audio-surveillance systems , 2007, 2007 IEEE Conference on Advanced Video and Signal Based Surveillance.

[35]  Jason Nolan,et al.  Sousveillance: Inventing and Using Wearable Computing Devices for Data Collection in Surveillance Environments. , 2002 .

[36]  Hille Koskela,et al.  ‘The gaze without eyes’: video-surveillance and the changing nature of urban space , 2000 .

[37]  Sen-Ching S. Cheung,et al.  Video Data Hiding for Managing Privacy Information in Surveillance Systems , 2009, EURASIP J. Inf. Secur..

[38]  Catalin Grigoras.  Digital audio recording analysis: the Electric Network Frequency (ENF) Criterion , 2005 .

[39]  Touradj Ebrahimi,et al.  H.264/AVC video scrambling for privacy protection , 2008, 2008 15th IEEE International Conference on Image Processing.

[40]  A. Hampapur,et al.  Smart video surveillance: exploring the concept of multiscale spatiotemporal tracking , 2005, IEEE Signal Processing Magazine.

[41]  David A. Pollock.  Methods of Electronic Audio Surveillance , 1972 .

[42]  Faisal Z. Qureshi,et al.  Object-Video Streams for Preserving Privacy in Video Surveillance , 2009, 2009 Sixth IEEE International Conference on Advanced Video and Signal Based Surveillance.

[43]  Michael J. Black,et al.  HumanEva: Synchronized Video and Motion Capture Dataset and Baseline Algorithm for Evaluation of Articulated Human Motion , 2010, International Journal of Computer Vision.

[44]  Malcolm Kirkup,et al.  Video surveillance research in retailing: ethical issues , 2000 .

[45]  John G. Apostolopoulos,et al.  Secure scalable streaming enabling transcoding without decryption , 2001, Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205).

[46]  Anil K. Jain,et al.  Text information extraction in images and video: a survey , 2004, Pattern Recognit..

[47]  B. Loader,et al.  Cybercrime : law enforcement, security and surveillance in the information age , 2000 .

[48]  Guo-Qiang Han,et al.  The Application of Chaos and DWT in Image Scrambling , 2006, 2006 International Conference on Machine Learning and Cybernetics.

[49]  David Raths.  Video Surveillance: All Eyes Turn to IP. , 2011 .

[50]  Jianping Fan,et al.  A novel approach for privacy-preserving video sharing , 2005, CIKM '05.

[51]  Marta Vos,et al.  Establishing business integrity in an online environment: An examination of New Zealand web site privacy notices , 2009, Online Inf. Rev..

[52]  Paul A. Viola,et al.  Rapid object detection using a boosted cascade of simple features , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[53]  Susanne Lace,et al.  The glass consumer : life in a surveillance society , 2005 .

[54]  Ernesto Andrade,et al.  Simulation of Crowd Problems for Computer Vision , 2005 .

[55]  Hyeonjoon Moon,et al.  The FERET Evaluation Methodology for Face-Recognition Algorithms , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[56]  Larry S. Davis,et al.  Real-time foreground-background segmentation using codebook model , 2005, Real Time Imaging.

[57]  Stefano Tubaro,et al.  Subjective Quality Assessment of H.264/AVC Video Streaming with Packet Losses , 2011, EURASIP J. Image Video Process..

[58]  Demetri Terzopoulos,et al.  Autonomous pedestrians , 2007, Graph. Model..

[59]  Demetri Terzopoulos,et al.  Smart Camera Networks in Virtual Reality , 2008, Proc. IEEE.

[60]  Jake K. Aggarwal,et al.  Human Motion Analysis: A Review , 1999, Comput. Vis. Image Underst..

[61]  Heiko Schwarz,et al.  Overview of the Scalable Video Coding Extension of the H.264/AVC Standard , 2007, IEEE Transactions on Circuits and Systems for Video Technology.

[62]  swright.  Privacy and Surveillance Post-9/11 , 2011 .

[63]  Richard S. Julie.  High-Tech Surveillance Tools and the Fourth Amendment: Reasonable Expectations of Privacy in the Technological Age , 2000 .

[64]  Robert N. Strassfeld,et al.  Foreword: Somebody’s Watching Me: Surveillance and Privacy in an Age of National Insecurity , 2010 .

[65]  Matthew N. Dailey,et al.  Multiple human tracking in high-density crowds , 2009, Image Vis. Comput..

[66]  Isarin Promyarut,et al.  Video Scrambling for Privacy Protection in Surveillance System , .

[67]  Mitchell Gray,et al.  Urban Surveillance and Panopticism: will we recognize the facial recognition society? , 2002 .

[68]  Tony Millett.  Copyright Guidelines for Research Students , 2008 .

[69]  Andrew Senior.  Protecting Privacy in Video Surveillance , 2009 .

[70]  Benjamin B. Kimia,et al.  Deblurring Gaussian blur , 2015, Comput. Vis. Graph. Image Process..

[71]  Jonathan Brandt,et al.  Robust object detection via soft cascade , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[72]  Mubarak Shah,et al.  A Lagrangian Particle Dynamics Approach for Crowd Flow Segmentation and Stability Analysis , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

[73]  Mohan S. Kankanhalli,et al.  Privacy modeling for video data publication , 2010, 2010 IEEE International Conference on Multimedia and Expo.

[74]  Sharath Pankanti,et al.  Enabling video privacy through computer vision , 2005, IEEE Security & Privacy Magazine.

[75]  Mohan S. Kankanhalli,et al.  W3-privacy: understanding what, when, and where inference channels in multi-camera surveillance video , 2012, Multimedia Tools and Applications.