Rule-based real-time detection of context-independent events in video shots

Amer, A.; Dubois, Éric; Mitiche, Amar

doi:10.1016/j.rti.2004.12.001

Cited by 12 publications

(9 citation statements)

References 23 publications

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“…using [6]) and their physical characteristics (e.g., size, shape, position, and motion) and associated video events (e.g., moving, stay long, is inside, and disappear) are available (e.g. using [7]). We assume that a video object has a unique identifier (ID maintained by a tracking algorithm) for the whole input video sequence.…”

Section: ) Predefined Restricted Region (R R ): the Detectionmentioning

confidence: 99%

Real-time automatic detection of vandalism behavior in video sequences

Ghazal

Vázquez

Amer

2007

2007 IEEE International Conference on Systems, Man and Cybernetics

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This paper proposes a method for the realtime detection of vandalism in video sequences. The proposed method detects vandalism through the robust extraction of a sequence of high-level events leading to it without resorting to object recognition and using a single camera. Vandalism is declared when an object enters the scene and causes an unauthorized change inside a predefined vandalisable area in the scene such as a pay phone or a sign. The proposed method was tested offline and on-line and our results show that it is robust in detecting vandalism or graffiti in surveillance video sequences.

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Section: ) Predefined Restricted Region (R R ): the Detectionmentioning

confidence: 99%

Real-time automatic detection of vandalism behavior in video sequences

Ghazal

Vázquez

Amer

2007

2007 IEEE International Conference on Systems, Man and Cybernetics

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“…Video Workstations are then responsible for processing the captured video to extract events from the scene. The proposed system uses the methods in [1] to extract surveillance events. The video signal is then compressed and sent using multicast to Control Workstations via the Real Time Streaming Protocol (RTSP).…”

Section: System Overviewmentioning

confidence: 99%

“…The video signal is then processed by C p vi using the algorithm in [1] to detect surveillance events such as object occluding or approaching restricted sites.…”

Section: Video Worktationmentioning

confidence: 99%

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A Modular Distributed Video Surveillance System Over IP

Ostheimer

Lemay

Ghazal

et al. 2006

2006 Canadian Conference on Electrical and Computer Engineering

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We present an automated and distributed real-time video surveillance system which can be used for the detection of objects and events in a wide range of applications. Video feeds are captured from multiple sources, processed and streamed over the Internet for viewing and analysis. Components of the system can be interconnected in several manners, thus forming flexible systems. The experimental results show a system that handles multiple video feeds, running on standard computers and yielding fluid video. Several interconnected clients can view multiple feeds simultaneously, as well as the event listing.

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“…Figure 2 illustrates the architecture of the rule-based reasoning framework for video interpretation. As in [18,2] the starting point of the proposed approach is a (low-level) image processing module. Subsequently, fact generation and simple event detection is performed.…”

Section: Introductionmentioning

confidence: 99%

Rule-Based Video Interpretation Framework: Application to Automated Surveillance

Geerinck

Enescu

Ravyse

et al. 2009

2009 Fifth International Conference on Image and Graphics

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Video applications usually involve a large number of moving objects. Moving objects refer to semantic realworld entities denoting a coherent spatial region and being automatically computed by the continuity of spatial and temporal low-level features, such as color and motion. In surveillance application, spatial and temporal relationships among these objects should be efficiently supported and retrieved for abnormal event recognition. In this paper we emphasize on analyzing and interpreting video object motions for advanced surveillance application. We propose a rule-based system allowing moving objects description at the low level (spatio-temporal features and relationships) as well as at the semantic level (actions, events and interaction). The result of the proposed system is illustrated to detect context dependent events in surveillance.

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Rule-based real-time detection of context-independent events in video shots

Cited by 12 publications

References 23 publications

Real-time automatic detection of vandalism behavior in video sequences

Real-time automatic detection of vandalism behavior in video sequences

A Modular Distributed Video Surveillance System Over IP

Rule-Based Video Interpretation Framework: Application to Automated Surveillance

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