Rule-Based Video Interpretation Framework: Application to Automated Surveillance

Geerinck, Thomas; Enescu, Valentin; Ravyse, Ilse; Sahli, Hichem

doi:10.1109/icig.2009.140

Cited by 4 publications

(4 citation statements)

References 15 publications

(19 reference statements)

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“…SIMPOZ project aims at building a highly configurable video surveillance system utilizing recent results of research on intelligent video analysis [10,22,43,59], real-time video processing [36,37] and image understanding [62,63]. SIMPOZ is an acronym of the Polish project name that can be translated as: System of Intelligent Monitoring of Objects and Areas of Special Importance.…”

Section: Presentation Of the Simpoz Systemmentioning

confidence: 99%

Risk assessment for a video surveillance system based on Fuzzy Cognitive Maps

Szwed

Skrzynski

Chmiel

2014

Multimed Tools Appl

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For various IT systems security is considered a key quality factor. In particular, it might be crucial for video surveillance systems, as their goal is to provide continuous protection of critical infrastructure and other facilities. Risk assessment is an important activity in security management; it aims at identifying assets, threats and vulnerabilities, analysis of implemented countermeasures and their effectiveness in mitigating risks. This paper discusses an application of a new risk assessment method, in which risk calculation is based on Fuzzy Cognitive Maps (FCMs) to a complex automated video surveillance system. FCMs are used to capture dependencies between assets and FCM based reasoning is applied to aggregate risks assigned to lower-level assets (e.g. cameras, hardware, software modules, communications, people) to such high level assets as services, maintained data and processes. Lessons learned indicate, that the proposed method is an efficient and lowcost approach, giving instantaneous feedback and enabling reasoning on effectiveness of security system.

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Section: Presentation Of the Simpoz Systemmentioning

confidence: 99%

Risk assessment for a video surveillance system based on Fuzzy Cognitive Maps

Szwed

Skrzynski

Chmiel

2014

Multimed Tools Appl

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“…In the domain of automatic scenarios identification in the video sequence, a number of interesting results can be found in the work of F. Bremond [2] and M. Thonnat [5]. An interesting application of rule-based systems in automatic surveillance systems was presented by Geerinck [6].…”

Section: Introductionmentioning

confidence: 99%

Realization of Scenarios for Video Surveillance

Chmiel

Kwiecień

Mikrut

2012

Image Processing & Communications

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The design of a methodology for the effective scene understanding systems is one of the main goals of the researchers in the analysis of video surveillance. The objects in the scene have to be identified. Hence, it is necessary to detect the parts belonging to the background. In the article we introduce the base algorithms, which enable us to realization of scenarios. We briefly describe base algorithms (object detection, object localization, recognition of humans, movement detection and configuration of scene) used in three selected scenarios: violation of protected zones, abandoned objects and vandalism (graffiti). These scenarios were tested on several films, obtained from Internet and made by participants of project SIMPOZ. The results of our experiments are presented. The basic algorithms for detecting and locating objects are very quickly, but movement detection ("optical flow") and recognition of humans algorithms work longer.

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“…Using time intervals and logical formalisms, previous approaches have obtained successful results in detecting high level activities [1]. Formal rules have been defined for detecting activities involving interactions amongst people or recognize unusual behaviors of individuals [2,3]. More recently, an expert system was used to combine facts detected by a low-level framework, and inference rules previously defined by an expert [4].…”

Section: Introductionmentioning

confidence: 99%

A Fuzzy Spatio-temporal-Based Approach for Activity Recognition

Yaouanc

Poli

2012

Lecture Notes in Computer Science

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Abstract. Over the last decade, there has been a significant deployment of systems dedicated to surveillance. These systems make use of real-time sensors that generate continuous streams of data. Despite their success in many cases, the increased number of sensors leads to a cognitive overload for the operator in charge of their analysis. However, the context and the application requires an ability to react in real-time. The research presented in this paper introduces a spatio-temporal-based approach the objective of which is to provide a qualitative interpretation of the behavior of an entity (e.g., a human or vehicle). The process is formally supported by a fuzzy logic-based approach, and designed in order to be as generic as possible.

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Rule-Based Video Interpretation Framework: Application to Automated Surveillance

Cited by 4 publications

References 15 publications

Risk assessment for a video surveillance system based on Fuzzy Cognitive Maps

Risk assessment for a video surveillance system based on Fuzzy Cognitive Maps

Realization of Scenarios for Video Surveillance

A Fuzzy Spatio-temporal-Based Approach for Activity Recognition

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