A distributed camera system for multi-resolution surveillance
Nicola Bellotto,Eric Sommerlade,Ben Benfold,Charles Bibby,Ian Reid,Daniel Roth,Carles Fernández,Luc Van Gool,Jordi Gonzàlez +8 more
- 20 Oct 2009
- pp 1-8
TL;DR: An architecture for a multi-camera, multi-resolution surveillance system to support a set of distributed static and pan-tilt-zoom cameras and visual tracking algorithms, together with a central supervisor unit is described.
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Abstract: We describe an architecture for a multi-camera, multi-resolution surveillance system. The aim is to support a set of distributed static and pan-tilt-zoom (PTZ) cameras and visual tracking algorithms, together with a central supervisor unit. Each camera (and possibly pan-tilt device) has a dedicated process and processor. Asynchronous interprocess communications and archiving of data are achieved in a simple and effective way via a central repository, implemented using an SQL database.
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Citations
Handbook of Face Recognition
Stan Z. Li,Anil K. Jain +1 more
- 31 Aug 2011
TL;DR: This highly anticipated new edition provides a comprehensive account of face recognition research and technology, spanning the full range of topics needed for designing operational face recognition systems, as well as offering challenges and future directions.
Adaptive Fuzzy Particle Filter Tracker for a PTZ Camera in an IP Surveillance System
TL;DR: Results show that the AFPF method applied to a human-tracking application in an IP PTZ surveillance system has good target-detection precision, low track fragmentation, and a high processing rate, and the target is almost always located within one-sixth of the image diameter from the image center.
58
Semi-supervised intelligent surveillance system for secure environments
Clinton Fookes,Simon Denman,Ruan Lakemond,David Ryan,Sridha Sridharan,Massimo Piccardi +5 more
- 04 Jul 2010
TL;DR: In this article, a semi-supervised intelligent visual surveillance system is proposed to exploit the information from multi-camera networks for the monitoring of people and vehicles, which can perform critical surveillance tasks including tracking of objects across multiple views, recognition of people utilizing biometrics and in particular soft-biometrics, monitoring of crowds, and activity recognition.
Cognitive visual tracking and camera control
Nicola Bellotto,Ben Benfold,Hanno Harland,Hans-Hellmut Nagel,Nicola Pirlo,Ian Reid,Eric Sommerlade,Chuan Zhao +7 more
TL;DR: An efficient solution to extract, in real-time, high-level information from an observed scene, and generate the most appropriate commands for a set of pan-tilt-zoom (PTZ) cameras in a surveillance scenario is presented.
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Automatic surveillance in transportation hubs
TL;DR: In this paper, a conceptual framework combining security and operations is proposed to support real-time measurements of queues and crowding in spaces, but have been installed as system add-ons (rather than making better use of existing infrastructure), resulting in expensive infrastructure outlay for the owner/operator, and an overload of surveillance systems which in itself creates further complexity.
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References
Rapid object detection using a boosted cascade of simple features
Paul A. Viola,Michael Jones +1 more
- 01 Dec 2001
TL;DR: A machine learning approach for visual object detection which is capable of processing images extremely rapidly and achieving high detection rates and the introduction of a new image representation called the "integral image" which allows the features used by the detector to be computed very quickly.
Multitarget-Multisensor Tracking: Principles and Techniques
Yakov Bar-Shalom,Xiao Rong-Li +1 more
- 01 Jan 1995
2.6K
Into the woods: visual surveillance of noncooperative and camouflaged targets in complex outdoor settings
Terrance E. Boult,Ross J. Micheals,Xiang Gao,Michael Eckmann +3 more
- 01 Oct 2001
TL;DR: The primary focus of the paper is the Lehigh Omnidirectional Tracking System (LOTS) and its components, which includes adaptive multibackground modeling, quasi-connected components (a novel approach to spatio-temporal grouping), background subtraction analyses, and an overall system evaluation.
Comparison of target detection algorithms using adaptive background models
Daniela Hall,Jacinto C. Nascimento,Pedro Ribeiro,E. Andrade,Plinio Moreno,S. Pesnel,Thor List,Rémi Emonet,Robert B. Fisher,J.S. Victor,James L. Crowley +10 more
- 15 Oct 2005
TL;DR: This article compares the performance of target detectors based on adaptive background differencing on public benchmark data with state of the art measures with respect to ground truth.
Face cataloger: multi-scale imaging for relating identity to location
Arun Hampapur,Sharath Pankanti,Andrew W. Senior,Yingli Tian,Lisa M. Brown,Rudolf Maarten Bolle +5 more
- 21 Jul 2003
TL;DR: This work uses computer controlled pan-tilt-zoom cameras driven by a 3D wide-baseline stereo tracking system to address the "who is where" problem.