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conference on Multisensor, Multisource Information fusion

作者： Hsu, D. Frank Lyons, Damian M. Ai, Jizhou Fordham Univ Dept Comp & Informat Sci Robot & Comp Vis Lab Bronx NY 10458 USA

ISBN: (纸本)0819462985

We address the problem of selecting features to improve automated video tracking of targets that undergo multiple mutual occlusions. As targets are occluded, different feature subsets and combinations of those features are effective in identifying the target and improving tracking performance. We use Combinatorial fusion Analysis to develop a metric to dynamically select which subset of features will produce the most accurate tracking. In particular we show that the combination of a pair of features A and B will improve the accuracy only if (a) A and B have relative high performance, and (b) A and B are diverse. We present experimental results to illustrate the performance of the proposed metric.

关键词： video surveillance target tracking feature selection sensory fusion

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On handling dependent evidence and multiple faults in knowledge fusion for engine health management

On handling dependent evidence and multiple faults in knowle...

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2006 IEEE Aerospace conference

作者： Guralnik, Valerie Mylaraswamy, Dinkar Voges, Hal Honeywell Labs 3660 Technol Dr Minneapolis MN 55418 USA

ISBN: (纸本)078039545X

Diagnostic architectures that fuse outputs from multiple algorithms are described as knowledge fusion or evidence aggregation. Knowledge fusion using a statistical framework such as Dempster-Shafer (D-S) has been used in the context of engine health management. Fundamental assumptions made by this approach include the notion of independent evidence and single fault. In most real world systems, these assumptions are rarely satisfied. Relaxing the single fault assumption in D-S based knowledge fusion involves working with a hyper-power set of the frame of discernment. Computational complexity limits the practical use of such extension. In this paper, we introduce the notion of mutually exclusive diagnostic subsets. In our approach, elements of the frame of discernment are subsets of faults that cannot be mistaken for each other, rather than failure modes. These subsets are derived using a systematic analysis of connectivity and causal relationship between various components within the system. Specifically, we employ a special form of reachability analysis to derive such subsets. The theory of D-S can be extended to handle dependent evidence for simple and separable belief functions. However, in the real world the conclusions of diagnostic algorithms might not take the form of simple or separable belief functions. In this paper, we present a formal definition of algorithm dependency based on three metrics: the underlying technique an algorithm is using, the sensors it is using, and the feature of the sensor that the algorithm is using. With this formal definition, we partition evidence into highly dependent, weakly dependent, and independent evidence. We present examples from a Honeywell auxiliary power unit to illustrate our modified D-S method of evidence aggregation.

关键词： Knowledge management

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Spectral signature calculations and target tracking for remote sensing

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IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT 2006年第4期55卷 1430-1442页

作者： Yeary, Mark B. Zhai, Yan Yu, Tian-You Nematifar, Shamim Shapiro, Alan Univ Oklahoma DSP & Embedded Syst Lab Dept Elect & Comp Engn Norman OK 73019 USA Univ Oklahoma Sch Metorol Norman OK 73019 USA

Enhanced tornado detection and tracking can prevent loss of life and property damage. The research weather surveillance radar (WSR)-88D locally operated by the National Severe Storms Laboratory (NSSL) in Norman, OK, has the unique capability of collecting massive volumes of time-series data over many hours, which provides a rich environment for evaluating our new postprocessing algorithms. With the advent of more memory and computing power, new state-of-the-art algorithms can be explored. In this paper, an approach of identifying tornado vortices in Doppler spectra is proposed and investigated through the use of neural networks. Once the coordinate of the tornado has been established, the research question becomes the following: Can we apply target tracking algorithms to a volume of radar data to make estimations about where the tornado is going? In recent years, particle filters have attracted great attention in several research communities. These filters are used in problems where time-varying signals must be processed in real time, and the objective is to estimate various unknowns of the signals and to detect events described by, the signals. The standard solutions of such problems in many applications are based on the Kalman or extended Kalman filters. In situations when the models that describe the behavior of the system are highly nonlinear and/or the noise that distorts the signals is non-Gaussian, the Kalman-filter-based algorithms provide solutions that may be far from optimal. Here, the path of the tornado follows a path that may be described by a set of nonlinear equations. To estimate the path, the particle filter will provide the better estimates. In addition to the single WSR-88D sensor designs, data fusion and tracing designs are also given for a four-node remote sensor network in central Oklahoma. By incorporating the data from each of the sensors, improvements in tracking are illustrated. The particle-filtering algorithms are especially effective in

关键词： digital signal processing National Weather Radar Testbed (NWRT) particle filters radar measurements real-time sensor instrumentation remote sensing sensor networks spectral signature calculations state estimation weather surveillance radar (WSR)-88D (KOUN) radar

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Realizing Situation Awareness in a cyber environment

Realizing Situation Awareness in a cyber environment

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conference on Multisensor, Multisource Information fusion

作者： Tadda, George Salerno, John J. Boulware, Douglas Hinman, Michael Gorton, Samuel USAF Res Lab 525 Brooks Rd Rome NY 13441 USA Skaion Corp North Chelmsford MA 01863 USA

ISBN: (纸本)0819462985

Situation Awareness (SA) problems all require an understanding of current activities, an ability to anticipate what may happen next, and techniques to analyze the threat or impact of current activities and predictions. These processes of SA are common regardless of the domain and can be applied to the detection of cyber attacks. This paper will describe the application of a SA framework to implementing Cyber SA, describe some metrics for measuring and evaluating systems implementing Cyber SA, and discuss ongoing work in this area. We conclude with some ideas for future activities.

关键词： advanced fusion situation awareness Cyber Situation Awareness

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Pedestrian detection by Multi-spectral fusion

Pedestrian detection by Multi-spectral fusion

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conference on Multisensor, Multisource Information fusion

作者： Ma, Yunqian Wang, Zheng Bazakos, Mike Honeywell Labs 3660 Technol Dr Minneapolis MN 55418 USA Honeywell Technol Solut Lab Shanghai 201203 Peoples R China

ISBN: (纸本)0819462985

Security systems increasingly rely on the use of Automated Video Surveillance (AVS) technology. In particular the use of digital video renders itself to internet and local communications, remote monitoring, and to computer processing. AVS systems can perform many tedious and repetitive tasks currently performed by trained security personnel. AVS technology has already made some significant steps towards automating some basic security functions such as: motion detection, object tracking and event-based video recording. However, there are still many problems associated with just these automated functions, which need to be addressed further. Some examples of these problems are: the high "false alarm rate" and the "loss of track" under total or partial occlusion, when used under a wide range of operational parameters (day, night, sunshine, cloudy, foggy, range, viewing angle, clutter, etc.). Current surveillance systems work well only under a narrow range of operational parameters. Therefore, they need be hardened against a wide range of operational conditions. In this paper, we present a Multi-spectral fusion approach to perform accurate pedestrian segmentation under varying operational parameters. Our fusion method combines the "best" detection results from the visible images and the "best" from the thermal images. Commonly, the motion detection results in the visible images are easily affected by noise and shadows. The objects in the thermal image are relatively stable, but they may be missing some parts of the objects, because they thermally blend with the background. Our method makes use of the "best" object components and de-emphasize the "not best".

关键词： pedestrian detection sensor fusion surveillance level set

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MeRIS and ETM image fusion for spatial resolution improvement

MeRIS and ETM image fusion for spatial resolution improvemen...

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conference on Multisensor, Multisource Information fusion

作者： Minghelli-Roman, Audrey Mathieu, Sandrine Polidori, Laurent Loubersac, Lionel Cauneau, Francois Univ Bourgogne CNRS UMR 5158 LE21 F-21078 Dijon France Alcatel Alenia Space Ind F-06156 Cannes France IRD Lab Reg Teledetect Cayenne 97323 French Guiana IFREMER DEL DRV LER LR F-34203 Sete France Ecole Mines Paris Ctr Energetique Grp T&M F-06904 Sophia Antipolis France

ISBN: (纸本)0819462985

MeRIS was launched in March 2002 and has been providing images since June 2002. Before its launch, we had implemented a method to improve its resolution by merging its images with Landsat ETM images in order to preserve the best characteristics of the two images (spatial, spectral, temporal). We now present the results of this method for real MeRIS images (level 1b and 2) in a coastal area. The robustness of the method is studied as well as the influence of the delay between the acquisitions of the two images

关键词： fusion ETM MeRIS

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Adaptive sampling using non-linear EKF with mobile robotic wireless sensor nodes

Adaptive sampling using non-linear EKF with mobile robotic w...

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9th International conference on Control, Automation, Robotics and Vision

作者： Popa, D. O. Mysorewala, M. F. Lewis, F. L. Univ Texas Arlington Automat & Robot Res Inst Arlington TX 76019 USA

ISBN: (纸本)9781424403417

The use of robotics in distributed monitoring applications requires mobile wireless sensors that are deployed efficiently. Efficiency can be defined in multiple ways, such as in terms of the amount of energy expenditure, communication bandwidth or information content. A very important aspect of mobile sensor deployment includes sampling algorithms at location most likely to yield useful information about a field variable of interest. In this paper, we use inexpensive mobile robot nodes built in our lab (ARRI-Bots) as wireless sensor deployment agents, and we use them to demonstrate information efficient algorithms (e.g., "adaptive sampling"). Each mobile robot node is characterized by sensor measurement noise in addition to localization uncertainty. We use the Extended Kalman Filter (EKF) to derive quantitative information measures for sampling locations most likely to yield optimal information about the sampled field distribution. We present simulation and experimental results using this approach.

关键词： adaptive sampling sensor fusion kahnan filter field distribution monitoring

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Scalable algorithms for aggregating disparate forecasts of probability

Scalable algorithms for aggregating disparate forecasts of p...

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9th International conference on Information fusion

作者： Predd, J. B. Kulkarni, S. R. Poor, H. V. Osherson, D. N. Princeton Univ Dept Elect Engn Princeton NJ 08544 USA Princeton Univ Dept Psychol Princeton NJ 08544 USA

ISBN: (纸本)9781424409532

In this paper, computational aspects of the panel aggregation problem are addressed. Motivated primarily by applications of risk assessment, an algorithm is developed for fusing large corpora of internally incoherent probability assessments. The algorithm is characterized by a provable performance guarantee, and is demonstrated to be orders of magnitude faster than existing tools when tested on several real-world data-sets. In addition, unexpected connections between research in risk assessment and wireless sensor networks are exposed, as several key ideas are illustrated to be useful in both fields.

关键词： aggregation forecasting fusion risk assessment sensor networks

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A preprocessing and automated algorithm selection system for image registration

A preprocessing and automated algorithm selection system for...

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conference on Multisensor, Multisource Information fusion

作者： Drozd, A. L. Blackburn, A. C. Kasperovich, I. P. Varshney, P. K. Xu, M. Kumar, B. Syracuse Univ Syracuse NY 13244 USA

ISBN: (纸本)0819462985

Image registration is a technique for precisely aligning the content of two or more images. It is often used as a preprocessing stage for further analysis, such as automatic target recognition, change detection, and environmental remote sensing. However, there are many different registration algorithms available to the image analyst, and it's difficult to know which one is the best one to use for a particular pair of images. These various algorithms also have a multitude of settings and parameters that must be given proper values for best results. Consequently, it is often difficult to know which algorithm will perform the best in a given situation, under constraints of time or accuracy. We propose constructing an expert system, with rules based on experimental results, that will automatically select the appropriate registration algorithm and perform appropriate preprocessing steps to prepare the images for registration.

关键词： image registration data fusion image processing expert systems

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Application-centric networking framework for wireless sensor nodes

Application-centric networking framework for wireless sensor...

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3rd Annual International conference on Mobile and Ubiquitous System - Networking and Services

作者： Choi, Sukwon Cha, Hojung Yonsei Univ Dept Comp Sci Seoul 120749 South Korea

ISBN: (纸本)9781424404988

Wireless sensor network technology has found diverse applications in numerous fields. As the networking technology is refined in many ways, the need for system modulation with effective performance becomes essential. A multitude of architectures, which includes system abstraction and layering, has been proposed to solve the need at the operating system level. However, previous efforts do not qualify for networking architecture required by sensor networking, since they are aimed at hardware abstraction or protocol-based layering. In this paper, we classify developers into kernel, network and application developers and propose a network architecture that enables those developers to program independently. Network stack is separated into three different layers;MLL, NSL, DNL. This three-layered architecture provides an effective programming environment to sensor network developers by minimizing modification of other layers and maximizing reusability of the networking module. To validate the proposed mechanism, we implemented and assessed the performance with a few network algorithms and applications, based on the RETOS, which supports a dynamic loadable kernel module.

关键词： Network architecture

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