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Active perception in a sensor fusion model

Active perception in a sensor fusion model

引用

conference on sensor fusion - architectures, algorithms, and applications VI

作者： Biel, L Wide, P Univ Orebro Ctr Appl Autonomous Sensor Syst Orebro Sweden

ISBN: (纸本)0819444812

During the last decades the research in the sensor fusion area has mainly been focused on fusion methods and feature selection methods. A possible further development in this area is to incorporate a process referred to as active perception. This means that the system is able to manipulate the sensing mechanisms to create a focus on selected information in the surrounding environment. This process may also be able to handle the feature selection process with respect to which features to be used and/or the number of features to use. This paper presents a model that contains a decision system based on active perception integrated with previous sensor fusion algorithms. The human body has perhaps one of the most advanced perceptual processing systems. The human perception process can be divided into sensation (measurement collection) and perception (interpret the surroundings). During the sensation process a huge amount of data is collected from different sensors that reflect the environment. The information has to be interpreted in an effective way, i.e. in the fusion process. The interpretation together with a decision system to control the sensors to focus on important information will correspond to the (active) perception process. The model presented in this paper capitalizes on the properties presented by the biological counterpart to achieve more human-like processes for a sensor fusion. Finally, the paper presents the testing of the model in two examples. The applications used have a safety approach of fire indication, identification and decision-making. The goal is to enlarge a conventional fire alarm system to not only detect fire, but also to propose different actions for a human in a dangerous area for example.

关键词： sensors sensor fusion Data fusion Fuzzy systems Carbon monoxide Oxygen Systems modeling Environmental sensing Control systems Signal processing

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fusion under the closed-world assumption

Fusion under the closed-world assumption

引用

conference on sensor fusion - architectures, algorithms, and applications V

作者： Grégoire, E Univ Sci & Tech Lille Flandres Artois CRIL F-62307 Lens France

ISBN: (纸本)0819440809

In this paper, new operators for fusing logical knowledge-bases (KBs) are proposed. They are defined in such a way that they can handle KBs that must be interpreted under forms of the closed-world assumption. Such assumptions implicitly augment the KBs with some additional information that could not be deduced using the standard logical deductive apparatus. More precisely, we extend previous recent works about the logical fusion of knowledge to handle such KBs. We focus on the model-theoretic definition of fusion operators to show their limits. In particular, the basic logical concept of model appears too coarse-grained. We solve this problem and propose new operators that cover a whole family of fusion approaches in the presence of variants of the closed-world assumption.

关键词： data fusion knowledge base fusion CWA nonmonotonic logics

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A linearly constrained least squares approach for multisensor data fusion

A linearly constrained least squares approach for multisenso...

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conference on sensor fusion - architectures, algorithms, and applications

作者： Zhou, YF Leung, H Telexis Corporation Canada Ottawa ON K1V 7P2 2427 Holly Lane Canada Surface Radar Section Defence Research Establishment Ottawa Ottawa ON K1A OK2 Canada

ISBN: (纸本)081942482X

In this paper, we present a linearly constrained least squares (LCLS) algorithm for multisensor data fusion. While fusion is considered in the scope of linear combination, the objective of the LCLS algorithm is to minimize the energy of the linearly fused information based on empirical sensory information. Statistical performance analysis of the LCLS algorithm will be carried out including the consistency and asymptotic covariance of the estimates. Effectiveness of the proposed fusion algorithm will be evaluated numerically based on fusion of signals and images.

关键词： data fusion least squares minimum variance information uncertainty multisensor tracking consistency analysis

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Multiple sources distributed information fusion based on multi-agent system

Multiple sources distributed information fusion based on mul...

引用

conference on sensor fusion - architectures, algorithms, and applications VI

作者： Xia, ZX E China Shipbldg Inst Dept Comp Sci Zhenjiang 212003 Peoples R China

ISBN: (纸本)0819444812

In a multi-node distributed decision system under some conditions there are few or none permitted information exchange between the nodes, this makes the information fusion and final decision difficult. However if we treat this distributed system as a multi-agent system, and each node acts as an agent, it has some other node's historical experiences or knowledge for resolving problems and stored in additional case bases, so it can uses case based reasoning (CBR) and transposition reasoning to obtain the possible viewpoints or decisions of other nodes and then makes information fusion by itself This approach may reduce the subjectivism which is the weakness of pure transposition reasoning.

关键词： distributed decision system multi-agent case based reasoning transposition reasoning

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Self-organized integration of adaptive visual cues for face tracking

Self-organized integration of adaptive visual cues for face ...

引用

conference on sensor fusion: architectures, algorithms, and applications iv

作者： Triesch, J Univ Rochester Dept Comp Sci Rochester NY 14627 USA

ISBN: (纸本)0819436771

The integration of information stemming from different sensors, cues, or modalities is among the most fundamental problems of perception in biological and artificial systems. Due to frequent changes in complex environments, the integration has to be adaptive. However, there usually is no teacher available to guide the adaptation. An agent has to figure out on his own which cues are reliable for a given task in the current context - self-organization is required. We have recently proposed a new integration scheme for such situations(1,2): In "Democratic Integration" the cues agree on a result and the result agreed upon serves as the basis for individual adaptations. A system with this property will automatically try to keep maximal coherence among its different cues. A technical formulation of this scheme has been employed in a face tracking system. The self-organized adaptation leads to suppression and recalibration of discordant cues, i.e., cues which do not agree with the overall result. Experiments show that the system is robust to sudden changes in the environment as long as the changes disrupt only a minority of the currently used cues at the same time, although all cues may be affected in the long run. The system relies partly on cues for which there was no a priori knowledge about the task available. These cues are bootstrapped by the others and can then keep the system on the right track during situations in which the original cues fail. In this paper we test and compare different measures of agreement between the overall result and individual cues' opinions, which serve as the basis for adapting a cue's weight in computing the overall result. Our results suggest, that adjusting a cue's weight in accordance to its current agreement to the overall result can only help if there is sufficient continuity in the cue's performance and may even be harmful otherwise.

关键词： computer vision sensor fusion sensory integration face tracking face detection self-organization adaptation Democratic Integration

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Fuzzy sensor fusion for gas turbine power plants

Fuzzy sensor fusion for gas turbine power plants

引用

conference on sensor fusion - architectures, algorithms, and applications III

作者： Goebel, K Agogino, A GE Corp Res & Dev Niskayuna NY 12309 USA

ISBN: (纸本)0819431931

In this paper we present a methodology for fuzzy sensor fusion. We then apply this methodology to sensor data from a gas turbine power plant. The developed fusion algorithm tackles several problems: 1.) it aggregates redundant (but uncertain) sensor information;this allows making decisions which sensors land to what degree) should be considered for propagation of sensor information. 2.) It filters out noise and sensor failure from measurements;this allows a system to operate despite temporary or permanent failure of one or more sensors. For the fusion, we use a combination of direct and functional redundancy. The fusion algorithm uses confidence values obtained for each sensor reading from validation curves and performs a weighted average fusion. With increasing distance from the predicted value, readings are discounted through a non-linear validation function. They are assigned a confidence value accordingly. The predicted value in the described algorithm is obtained through application of a fuzzy exponential weighted moving average time series predictor with adaptive coefficients. Experiments on real data from a gas turbine power plant show the robustness of the fusion algorithm which leads to smooth controller input values.

关键词： fuzzy fusion fuzzy validation fuzzy monitoring diagnosis

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Leveraging Provenance to Improve Data fusion in sensor Networks

Leveraging Provenance to Improve Data Fusion in Sensor Netwo...

引用

conference on Multisensor, Multisource Information fusion - architectures, algorithms, and applications

作者： Dogan, Gulustan Seo, Eunsoo Brown, Theodore Abdelzaher, Tarek F. CUNY New York NY 10021 USA Univ Illinois Urbana IL 61801 USA

ISBN: (纸本)9780819490858

Provenance is the information about the origin of the data inputs and the data manipulations to a obtain a final result. With the huge amount of information input and potential processing available in sensor networks, provenance is crucial for understanding the creation, manipulation and quality of data and processes. Thus maintaining provenance in a sensor network has substantial advantages. In our paper, we will concentrate on showing how provenance improves the outcome of a multi-modal sensor network with fusion. To make the ideas more concrete and to show what maintaining provenance provides, we will use a sensor network composed of binary proximity sensors and cameras to monitor intrusions as an example. Provenance provides improvements in many aspects such as sensing energy consumption, network lifetime, result accuracy, node failure rate. We will illustrate the improvements in accuracy of the position of the intruder in a target localization network by simulations.

关键词： Provenance Data fusion sensor Networks

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Multi-Layered Context Impact Modulation for Enhanced Focus of Attention of Situational Awareness in Persistent Surveillance Systems

Multi-Layered Context Impact Modulation for Enhanced Focus o...

引用

conference on Multisensor, Multisource Information fusion - architectures, algorithms and applications 2010

作者： Shirkhodaie, Amir Rababaah, Haroun Tennessee State Univ Dept Mech & Mfg Engn Ctr Excellence Battlefield Sensor Fus Nashville TN 37209 USA

ISBN: (纸本)9780819481740

This paper presents a Multi-Layered Context Impact Modulation (MCIM) technique for persistent surveillance systems (PSS) and discusses its layered architecture for different context modulations including: spatial, temporal, sensor reliability, human presence, and environmental modulations. This paper also presents a fusion model for enhancement of focus of attention at the common operation picture (COP). The fusion model combines all the impacts from the different MCIM layers onto one unified modulated map. To test and evaluate the performance of MCIM, several experiments were conducted to modulate interaction of humans and vehicles which exhibit various normal and suspicious behaviors. The experimental results show strength of this approach in correctly modulating different suspicious situations with higher degree of certainty.

关键词： Persistent Surveillance Systems Situation Assessment Context Impact Layered Modulation Energy Logic fusion Engine Large-scale sensor Networks Soft fusion

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Combination of fuzzy sets and Dempster-Shafer theories in forest map updating using multispectral data

Combination of fuzzy sets and Dempster-Shafer theories in fo...

引用

conference on sensor fusion - architectures, algorithms, and applications V

作者： Leduc, F Solaiman, B Cavayas, F ENST Bretagne Dept ITI F-29285 Brest France

ISBN: (纸本)0819440809

This paper explains a new approach to change detection and interpretation in a context of forest map updating. In this temporal change analysis we use a data set composed of map at time To and a satellite image at time T-1 and we refer to this as a mixed fusion approach. The analysis of remotely sensed data always necessitates the use of approximate reasoning. For this purpose, we use fuzzy logic to evaluate the objects' membership values to the considered classes and the Dempster-Shafer theory to analyse the confusion between classes and to find the more evident class to which an object belong.

关键词： map updating forestry change detection fuzzy logic Dempster-Shafer theory data fusion

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Information fusion for onboard and offboard avionics

Information fusion for onboard and offboard avionics

引用

conference on sensor fusion - architectures, algorithms, and applications II

作者： Kurien, T Chao, A Gully, SW Wood, A ALPHATECH Inc Burlington MA 01803 USA

ISBN: (纸本)0819428256

This paper defines and demonstrates an all-source information fusion system for combining onboard and offboard data and maintain continuous track on targets. We provide an architecture containing an offboard data processor to extract data relevant to the attack aircraft mission, and a set of fusion modules for recursively associating sensor reports, tracking targets, and classifying targets. These modules are derived from a well-posed mathematical formulation which enables us to define precise interfaces among the fusion modules. This approach provides three benefits. First, it enables us to construct a fusion algorithm with close-to-optimal target tracking and classification performance. Second, it allows us to study new fusion algorithms by implementing alternate algorithms for each module. Third, it allows us to process data from any combination of sensors making the architecture applicable to a variety of attack aircraft and missions. We show that the proposed system can increase a pilot's situational awareness by providing him with a clearer battlefield picture consistent with attack aircraft mission objectives. Results for a simple but realistic air-to-ground scenario simulation demonstrate the benefits of fusing data from offboard and onboard sensors.

关键词： all source fusion Multiple Hypothesis Tracking (MHT) image gee-registration continuous tracking onboard-offboard fusion Kalman filtering

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