On the effect of feedback in multilevel representation spaces for visual surveillance tasks

Carmona, Enrique J.; Rincón, M.; Bachiller, Margarita; Martínez-Cantos, Javier; Martínez‐Tomás, Rafael; Mira, José

doi:10.1016/j.neucom.2008.06.013

Cited by 10 publications

(9 citation statements)

References 9 publications

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“…This agent combines a system of perceiving images with vision software that requires high computational performance for near real‐time tasks. Its main functions are those of a vision system: segmentation, identification and tracking of people and/or objects within a monitored visual field (Carmona, ). For the identification process, a block‐based system is used (Folgado et al , ) developed by our group, the same as the level structure to identify events (Martínez‐Tomás et al , ).…”

Section: Intelligent Agents Of the Systemmentioning

confidence: 99%

“…This work presents a multi‐agent system for knowledge‐based high‐level event composition, which interprets activities, behaviour and situations semantically in a scenario with multi‐sensory monitoring. The system's specific aims would be (Bobick, ) to monitor the complex scenario, using all the sensors' capacities (Carmona, ) to interpret the information from these sources as a whole, and (Chleq & Thonnat, ) to request further information to confirm or reject the hypotheses raised in the process for diagnosing the situations.…”

Section: Introductionmentioning

confidence: 99%

“…Surveillance is a perfect application field for both plurisensory monitoring and interpreting video‐sequence scenes, where our group has accumulated considerable experience with AVISA project works (Folgado et al , ; Martínez‐Tomás et al , ; Carmona, ). It is also a multi‐disciplinary task affecting an increasing number of scenarios, services and clients.…”

Section: Introductionmentioning

confidence: 99%

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Multi-agent system for knowledge-based event recognition and composition

2011

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This work presents a multi-agent system for knowledge-based high-level event composition, which interprets activities, behaviour and situations semantically in a scenario with multi-sensory monitoring. A perception agent (plurisensory agent and visual agent)-based structure is presented. The agents process the sensor information and identify (agent decision system) significant changes in the monitored signals, which they send as simple events to the composition agent that searches for and identifies pre-defined patterns as higherlevel semantic composed events. The structure has a methodology and a set of tools that facilitate its development and application to different fields without having to start from scratch. This creates an environment to develop knowledge-based systems generally for event composition. The application task of our work is surveillance, and event composition=inference examples are shown which characterize an alarming situation in the scene and resolve identification and tracking problems of people in the scenario being monitored.

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Section: Intelligent Agents Of the Systemmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Multi-agent system for knowledge-based event recognition and composition

2011

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“…Within this context, our team began working with modular architecture that would support signal acquisition, signal fusion, and image processing (DeMarco 2009;Rivas, Martinez-Tomás, and Fernández-Caballero 2011;Rivas-Casado and Martinez-Tomás 2011;Carmona et al 2009). We developed an integral architecture called Horus (Castillo, Fernandez-Caballero, and Lopez 2011).…”

Section: Introductionmentioning

confidence: 99%

“…Our work for this article stems from the need to develop a mechanism that facilitates the description and modelling of scenes and situations that are based on the terminology and information (objects and events) obtained during the process of identifying and tracking objects of interest in a scene (Carmona et al 2009) (especially people) and during the identification of movements or activities of low semantic value such as entering in the field of vision of a camera, identified by RFID. All of these events are recognisable by multi-sensorial networks or by artificial vision systems.…”

Section: Introductionmentioning

confidence: 99%

Using semantic technologies and the OSU ontology for modelling context and activities in multi-sensory surveillance systems

Martínez‐Tomás

Tapia

et al. 2013

International Journal of Systems Science

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Automatic systems that monitor human behaviour for detecting security problems are a challenge today. Previously, our group defined the Horus framework, which is a modular architecture for the integration of multi-sensor monitoring stages. In this work, structure and technologies required for high-level semantic stages of Horus are proposed, and the associated methodological principles established with the aim of recognising specific behaviours and situations. Our methodology distinguishes three semantic levels of events: low level (compromised with sensors), medium level (compromised with context), and high level (target behaviours). The ontology for surveillance and ubiquitous computing has been used to integrate ontologies from specific domains and together with semantic technologies have facilitated the modelling and implementation of scenes and situations by reusing components. A home context and a supermarket context were modelled following this approach, where three suspicious activities were monitored via different virtual sensors. The experiments demonstrate that our proposals facilitate the rapid prototyping of this kind of systems.

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