Development of intelligent multisensor surveillance systems with agents

Pavón, Juán; Gómez-Sanz, Jorge J.; Fernández-Caballero, Antonio; Valencia-Jiménez, Julián J.

doi:10.1016/j.robot.2007.07.009

Cited by 97 publications

(83 citation statements)

References 21 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Where the random Eigen values is used as a parameter of the equation (11). The most correct alike finding of covarianceregion-of-interest classifies the needed image in the current image-frame.…”

Section: An Appropriate Alike Methodsmentioning

confidence: 99%

See 1 more Smart Citation

A Novel Stochastic Tracking Approach on Human Movement Analysis

AlamgirHossain¹,

Al-Turki²,

Sanyal³

2014

IJCA

View full text Add to dashboard Cite

Modern research demands more mathematical, statistical information and proves on the research topic. Moving Object tracking with mathematical and statistical approaches paves a new modus operandi stirring over the conventional methods. The use of covariance as a detector of object-based image to extract features is a proven approach. An object can be tracked by using the conventional histogram-based depiction model and it is a well known as well as a popular approach. Our proposed methodological model is build up with numerical, statistical and mathematical formulas. To implement them the standard images database collected images are considered. This mathematical model has been enriched in pursuance with covariance-chaser and in subsequently is capable enough to establish its supremacy with an eye to spawn an important algorithm leading to generate improved object-image-tracker (OIMT) method correctly by taking minimal finishing time. With the help of publicly available dataset enormous quantitative estimation is done pinpointing the efficacy of the reachable model. Our model is capable to achieve momentous speeding in humanobject-tracking dynamically in an enhanced way and this method is capable to decrease the error for false-tracking in comparison with the traditional histogram-based and other approaches. It is proved that the accuracy rate based on statistical-mathematical-detection-model (SMDM) is approximately 94.97% as compared to the MDM with 94.3% and the conventional model with 89.1%.

show abstract

Section: An Appropriate Alike Methodsmentioning

confidence: 99%

“…It is proposed to take more parameters to obtain the intensity-based-region of x and y. The requisite features can be acquired from the equation (11). λ Where R=Red, G=Green, B=Blue color and λ is the covariance-intensive-region.…”

Section: Image Recognitionmentioning

confidence: 99%

A Novel Stochastic Tracking Approach on Human Movement Analysis

AlamgirHossain¹,

Al-Turki²,

Sanyal³

2014

IJCA

View full text Add to dashboard Cite

show abstract

“…The use of intelligent agents is an essential component for analyzing information from distributed sensors [19] [15] [16]. These agents must be capable of both independent reasoning and joint analysis of complex situations in order to be able to achieve a high level of interaction with humans [5].…”

Section: General Description Of the Problemmentioning

confidence: 99%

Multi-Agent Architecture for Dependent Environments. Providing Solutions for Home Care

Fraile¹,

Bajo²,

Corchado³

2009

Int. Artif.

View full text Add to dashboard Cite

Obtaining novel and effective solutions for home care is one of the aims of Ambient Intelligence. Elderly and disabled people require special care services, and emerging technologies facilitate the development of intelligent environments in their homes. This paper presents AMADE, a multi-agent architecture for the control and supervision of home care environments. AMADE integrates an innovative alert management system as well as automated identification, location, and movement control systems. This study proposes a new perspective in tackling the problem of home care. An initial prototype based on the AMADE architecture was successfully tested in a real environment and the results obtained are presented within this paper.

show abstract

“…Yagnanarayana has used the concept of multimodal integration based on the superior colliculus and implemented it in various applications of an autoassociative neural network. According to J. Pavon [19], this multimodal integration concept is used to achieve efficiency in agents when co-operating and co-ordinating with various sensor data modalities. Similarly Rita Cucchiara [39] has established a biometric multimedia surveillance system that uses multimodal integration techniques for an effective surveillance system, but the multimodal usage is not able to overcome problems like the influence of noise.…”

Section: Introductionmentioning

confidence: 99%

Towards Computational Modelling of Neural Multimodal Integration Based on the Superior Colliculus Concept

Ravulakollu

Knowles

Liu

et al. 2009

Innovations in Neural Information Paradigms and Applications

View full text Add to dashboard Cite

Abstract. Information processing and responding to sensory input with appropriate actions are among the most important capabilities of the brain and the brain has specific areas that deal with auditory or visual processing. The auditory information is sent first to the cochlea, then to the inferior colliculus area and then later to the auditory cortex where it is further processed so that then eyes, head or both can be turned towards an object or location in response. The visual information is processed in the retina, various subsequent nuclei and then the visual cortex before again actions will be performed. However, how is this information integrated and what is the effect of auditory and visual stimuli arriving at the same time or at different times? Which information is processed when and what are the responses for multimodal stimuli? Multimodal integration is first performed in the Superior Colliculus, located in a subcortical part of the midbrain. In this chapter we will focus on this first level of multimodal integration, outline various approaches of modelling the superior colliculus, and suggest a model of multimodal integration of visual and auditory information.

show abstract

Development of intelligent multisensor surveillance systems with agents

Cited by 97 publications

References 21 publications

A Novel Stochastic Tracking Approach on Human Movement Analysis

A Novel Stochastic Tracking Approach on Human Movement Analysis

Multi-Agent Architecture for Dependent Environments. Providing Solutions for Home Care

Towards Computational Modelling of Neural Multimodal Integration Based on the Superior Colliculus Concept

Contact Info

Product

Resources

About