A multi-agent architecture to support active fusion in a visual sensor network

Castanedo, Federico; García, J.; Patricio, Miguel Á.; Molina, José M.

doi:10.1109/icdsc.2008.4635715

Cited by 12 publications

(11 citation statements)

References 16 publications

(16 reference statements)

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“…In Karlsson et al (2005), the agents that monitor objects of interest use information fusion of data gathered by multiple sensors. Related works use this technique to detect inconsistencies and improve the monitoring results (Castanedo et al, 2008;Remagnino et al, 2004).…”

Section: Multi-agents In Intelligent Surveillancementioning

confidence: 99%

A multi-agent architecture for supporting distributed normality-based intelligent surveillance

Vallejo

Albusac

Castro-Schez

et al. 2011

Engineering Applications of Artificial Intelligence

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Intelligent surveillance involves the use of AI techniques to monitor environments whose analysis is becoming more and more complex because of the large number of sensors used and the need of monitoring multiple events of interest simultaneously. Most of the current surveillance systems provide solutions for particular problems but still suffer from lack of flexibility and scalability when they are used on different or related surveillance problems. To overcome this limitation, two aspects should be addressed: a knowledge-based surveillance model flexible enough to deal with different events of interest and an architecture that gives support to this model when deploying the surveillance system within a particular scenario. This paper discusses the architecture devised to deploy intelligent surveillance systems by means of a set of autonomous agents that are responsible for the management of different surveillance tasks and for cooperating to monitor complex environments. This multi-agent architecture is inspired by a normality-based formal model used to define the knowledge needed to analyze general-purpose surveillance concepts. We use the architecture to deploy a surveillance system to monitor an urban traffic scenario.

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Section: Multi-agents In Intelligent Surveillancementioning

confidence: 99%

A multi-agent architecture for supporting distributed normality-based intelligent surveillance

Vallejo

Albusac

Castro-Schez

et al. 2011

Engineering Applications of Artificial Intelligence

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“…Finally, an interesting work regarding a network of software agents with visual sensors is presented in [31]. This system uses several cameras for recognition of users and tracking of their positions in an indoor space.…”

Section: Related Workmentioning

confidence: 99%

An Indoor Navigation System for the Visually Impaired

Guerrero

Vasquez

Ochoa

2012

Sensors

124

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Navigation in indoor environments is highly challenging for the severely visually impaired, particularly in spaces visited for the first time. Several solutions have been proposed to deal with this challenge. Although some of them have shown to be useful in real scenarios, they involve an important deployment effort or use artifacts that are not natural for blind users. This paper presents an indoor navigation system that was designed taking into consideration usability as the quality requirement to be maximized. This solution enables one to identify the position of a person and calculates the velocity and direction of his movements. Using this information, the system determines the user's trajectory, locates possible obstacles in that route, and offers navigation information to the user. The solution has been evaluated using two experimental scenarios. Although the results are still not enough to provide strong conclusions, they indicate that the system is suitable to guide visually impaired people through an unknown built environment.

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“…Therefore, the captured output information involves the machine vision subjects and image processing. The visual sensors (cameras) have distinguished features as they generate huge data, which needs local processing systems to transfer only the required date to represents in conceptualized level (Castanedo et al, ). In general, the image fusion technique combines the images from multiple sources to either single image or small set of images, which contains more useful and accurate information of surrounding in comparison to any individual source images.…”

Section: Introductionmentioning

confidence: 99%

Multifocus watermarking approach based on discrete cosine transform

Waheed

Alkawaz

Rehman

et al. 2016

Microsc. Res. Tech.

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Image fusion process consolidates data and information from various images of same sight into a solitary image. Each of the source images might speak to a fractional perspective of the scene, and contains both "pertinent" and "immaterial" information. In this study, a new image fusion method is proposed utilizing the Discrete Cosine Transform (DCT) to join the source image into a solitary minimized image containing more exact depiction of the sight than any of the individual source images. In addition, the fused image comes out with most ideal quality image without bending appearance or loss of data. DCT algorithm is considered efficient in image fusion. The proposed scheme is performed in five steps: (1) RGB colour image (input image) is split into three channels R, G, and B for source images. (2) DCT algorithm is applied to each channel (R, G, and B). (3) The variance values are computed for the corresponding 8 × 8 blocks of each channel. (4) Each block of R of source images is compared with each other based on the variance value and then the block with maximum variance value is selected to be the block in the new image. This process is repeated for all channels of source images. (5) Inverse discrete cosine transform is applied on each fused channel to convert coefficient values to pixel values, and then combined all the channels to generate the fused image. The proposed technique can potentially solve the problem of unwanted side effects such as blurring or blocking artifacts by reducing the quality of the subsequent image in image fusion process. The proposed approach is evaluated using three measurement units: the average of Q(abf), standard deviation, and peak Signal Noise Rate. The experimental results of this proposed technique have shown good results as compared with older techniques.

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A multi-agent architecture to support active fusion in a visual sensor network

Cited by 12 publications

References 16 publications

A multi-agent architecture for supporting distributed normality-based intelligent surveillance

A multi-agent architecture for supporting distributed normality-based intelligent surveillance

An Indoor Navigation System for the Visually Impaired

Multifocus watermarking approach based on discrete cosine transform

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