Towards a visual-hull based multi-agent surveillance system

Uson, Pilar Callau; Hagihara, Kaori; Ruiz, Diego; Macq, Benoı̂t

doi:10.1109/icip.2009.5414320

Cited by 2 publications

(1 citation statement)

References 8 publications

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“…(a) Using global features A system for behavior recognition of multiple humans in a scene, using multiple fish-eye cameras, is introduced by Uson et al 16 Utilization of multiple cameras and 3-D reconstruction aim in the elimination of ambiguities in observations. Each camera provides information about a partial model of the scene and they are merged to create a volumetric description of the scene.…”

Section: Generative Approachesmentioning

confidence: 99%

A First Stage Comparative Survey on Human Activity Recognition Methodologies

Tsitsoulis

Bourbakis

2013

Int. J. Artif. Intell. Tools

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The development of vision-based human activity recognition and analysis systems has been a matter of great interest to both the research community and practitioners during the last 20 years. Traditional methods that require a human operator watching raw video streams are nowadays deemed as at least ineffective and expensive. New, smart solutions in automatic surveillance and monitoring have emerged, propelled by significant technological advances in the fields of image processing, artificial intelligence, electronics and optics, embedded computing and networking, molding the future of several applications that can benefit from them, like security and healthcare. The main motivation behind it is to exploit the highly informative visual data captured by cameras and perform highlevel inference in an automatic, ubiquitous and unobtrusive manner, so as to aid human operators, or even replace them. This survey attempts to comprehensively review the current research and development on vision-based human activity recognition. Synopses from various methodologies are presented in an effort to garner the advantages and shortcomings of the most recent state-of-the-art technologies. Also a first-level self-evaluation of methodologies is also proposed, which incorporates a set of significant features that best describe the most important aspects of each methodology in terms of operation, performance and others and weighted by their importance. The purpose of this study is to serve as a reference for further research and evaluation to raise thoughts and discussions for future improvements of each methodology towards maturity and usefulness.

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Section: Generative Approachesmentioning

confidence: 99%

A First Stage Comparative Survey on Human Activity Recognition Methodologies

Tsitsoulis

Bourbakis

2013

Int. J. Artif. Intell. Tools

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Sudden Event Recognition: A Survey

Suriani

Hussain

Zulkifley

2013

Sensors

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Event recognition is one of the most active research areas in video surveillance fields. Advancement in event recognition systems mainly aims to provide convenience, safety and an efficient lifestyle for humanity. A precise, accurate and robust approach is necessary to enable event recognition systems to respond to sudden changes in various uncontrolled environments, such as the case of an emergency, physical threat and a fire or bomb alert. The performance of sudden event recognition systems depends heavily on the accuracy of low level processing, like detection, recognition, tracking and machine learning algorithms. This survey aims to detect and characterize a sudden event, which is a subset of an abnormal event in several video surveillance applications. This paper discusses the following in detail: (1) the importance of a sudden event over a general anomalous event; (2) frameworks used in sudden event recognition; (3) the requirements and comparative studies of a sudden event recognition system and (4) various decision-making approaches for sudden event recognition. The advantages and drawbacks of using 3D images from multiple cameras for real-time application are also discussed. The paper concludes with suggestions for future research directions in sudden event recognition.

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Towards a visual-hull based multi-agent surveillance system

Cited by 2 publications

References 8 publications

A First Stage Comparative Survey on Human Activity Recognition Methodologies

A First Stage Comparative Survey on Human Activity Recognition Methodologies

Sudden Event Recognition: A Survey

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