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Multi-camera networks : principles and applications /

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2009年

作者： Hamid Aghajan Andrea Cavallaro [editors].

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Real-Time Estimation of Roll Angle and CG Height for Active Rollover Prevention applications

Real-Time Estimation of Roll Angle and CG Height for Active ...

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2009 American Control Conference (ACC 2009)

作者： R. Rajamani D. Piyabongkarn v. Tsourapas J.Y. Lew University of Minnesota Minneapolis MN 55455 Eaton Corporation Innovation Center Eden Prairie MN 55344

ISBN: (纸本)9781424445233

Roll angle and height of the center of gravity are important variables that play a critical role in the calculation of real-time rollover index for a vehicle. The rollover index predicts the real-time propensity for rollover and is used in activation of rollover prevention systems such as differential braking based stability control systems. sensors to measure roll angle are expensive. sensors to estimate the c.g. height of a vehicle do not exist. While the height of the center-of-gravity does not change in real-time, it does change with the number of passengers and loading of the vehicle. This paper focuses on algorithms to estimate roll angle and c.g. height. The algorithms investigated include a sensor fusion algorithm that utilizes a low frequency tilt angle sensor and a gyroscope and a dynamic observer that utilizes only a lateral accelerometer and a gyroscope. The performance of the developed algorithms is investigated using simulations and experimental tests. Experimental data confirm that the developed algorithms perform reliably in a number of different maneuvers that include constant steering, ramp steering, double lane change and sine with dwell steering tests.

关键词： Character generation vehicles sensor fusion Gyroscopes Testing Gravity Real time systems Stability Control systems Goniometers

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Multi-algorithm fusion with template protection

Multi-algorithm fusion with template protection

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IEEE International Conference on Biometrics: Theory, applications, and Systems (BTAS)

作者： E.J.C. Kelkboom X. Zhou J. Breebaart R.N.J. veldhuis C. Busch Philips Research Netherlands Fraunhofer Institute for Computer Graphics Research IGD Germany Faculty EEMCS University of Twente Netherlands

The popularity of biometrics and its widespread use introduces privacy risks. To mitigate these risks, solutions such as the helper-data system, fuzzy vault, fuzzy extractors, and cancelable biometrics were introduced, also known as the field of template protection. In parallel to these developments, fusion of multiple sources of biometric information have shown to improve the verification performance of the biometric system. In this work we analyze fusion of the protected template from two 3D recognition algorithms (multi-algorithm fusion) at feature-, score-, and decision-level. We show that fusion can be applied at the known fusion-levels with the template protection technique known as the Helper-Data System. We also illustrate the required changes of the helper-data system and its corresponding limitations. Furthermore, our experimental results, based on 3D face range images of the FRGC v2 dataset, show that indeed fusion improves the verification performance.

关键词： Protection Biometrics Fuzzy systems Fingerprint recognition Data mining Iris Biosensors sensor phenomena and characterization Privacy Algorithm design and analysis

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Medical Image Registration Using Genetic Algorithm

Medical Image Registration Using Genetic Algorithm

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International Conference on Emerging Trends in Engineering and Technology, ICETET

作者： v. T. Ingole C. N. Deshmukh Anjali Joshi Deepak Shete PRMIT Badnera India PRMITR Badnera India Thakur College of Engineering Mumbai India

In many image-processing applications it is necessary to register multiple images of the same scene acquired by different sensors, or images taken by the same sensor but at different times. Mathematical modeling techniques are used to correct the geometric errors like translation, scaling and rotation of the input image to that of the reference image, so that these images can be used in various applications like change detection, image fusion etc. In the conventional methods, these errors are corrected by taking control points over the image and these points are used to establish the mathematical model. This paper addresses the image registration problem applying genetic algorithms. The image registration's objective is to define mapping that best match two set of points or images. In this work the point matching problem was addressed employing a method based on nearest-neighbor. The mapping was handled by affine transformations.

关键词： Biomedical imaging Image registration Genetic algorithms Image sensors Educational institutions Mathematical model Error correction Image fusion Application software Genetic mutations

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A recursive multi-scale correlation-averaging algorithm for synchronization and fusion of independent pavement roughness measurements

A recursive multi-scale correlation-averaging algorithm for ...

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International Conference on Intelligent Transportation

作者： Mandoye Ndoye Alan M. Barker James v. Krogmeier Darcy M. Bullock Schools of Civil Engineering and Electrical and Computer Engineering Purdue University West Lafayette IN USA

A signal processing approach is proposed to jointly filter and fuse spatially-indexed measurements captured from many vehicles. It is assumed that these measurements are corrupted by both sensor noise and GPS positioning uncertainties. Measurements from low-cost vehicle-mounted sensors (e.g., accelerometers and GPS receivers) are properly combined to produce higher quality road roughness data for cost-effective road surface condition monitoring. The proposed algorithms are recursively implemented and thus require only moderate computational power and memory space. These algorithms are important for future road management systems, which will use on-road vehicles as a distributed network of sensing probes gathering spatially-indexed measurements for condition monitoring in addition to other applications such as environmental monitoring. Our method and the related signal processing algorithms are tested using field data.

关键词： Signal processing algorithms Roads Condition monitoring Global Positioning System Filters Fuses vehicles Position measurement Noise measurement Measurement uncertainty

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Decision fusion in sensor Networks for Spectrum Sensing based on Likelihood Ratio Tests

Decision Fusion in Sensor Networks for Spectrum Sensing base...

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Conference on Advanced Signal Processing algorithms, architectures, and Implementantions XvIII

作者： Chung, Wei-Ho Yao, Kung Univ Calif Los Angeles Dept Elect Engn Los Angeles CA 90095 USA

ISBN: (纸本)9780819472946

sensor networks have been shown to be useful in diverse applications. One of the important applications is the collaborative detection based on multiple sensors to increase the detection performance. To exploit the spectrum vacancies in cognitive radios, we consider the collaborative spectrum sensing by sensor networks in the likelihood ratio test (LRT) frameworks. In the LRT, the sensors make individual decisions. These individual decisions are then transmitted to the fusion center to make the final decision, which provides better detection accuracy than the individual sensor decisions. We provide the lowered-bounded probability of detection (LBPD) criterion as an alternative criterion to the conventional Neyman-Pearson (NP) criterion. In the LBPD criterion, the detector pursues the minimization of the probability of false alarm while maintaining the probability of detection above the pre-defined value. In cognitive radios, the LBPD criterion limits the probabilities of channel conflicts to the primary users. Under the NP and LBPD criteria, we provide explicit algorithms to solve the LRT fusion rules, the probability of false alarm, and the probability of detection for the fusion center. The fusion rules generated by the algorithms are optimal under the specified criteria. In the spectrum sensing, the fading channels influence the detection accuracies. We investigate the single-sensor detection and collaborative detections of multiple sensors under various fading channels, and derive testing statistics of the LRT with known fading statistics.

关键词： sensor networks cognitive radio lower-bounded probability of detection criterion Neyman-Pearson criterion decision fusion

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Special issue on information fusion in distributed sensor networks

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INFORMATION fusion 2008年第3期9卷 330-331页

作者： Biswas, Pratik K. Hussain, Sajid Telcordia Technol Inc Appl Res Piscataway NJ 08854 USA Acadia Univ Wolfville NS B4P 2R6 Canada

The convergence of internet, wireless communications, and information processing technologies with techniques for miniaturization has opened up new vistas of research for sensor networks. Distributed sensor networks represent an evolving frontier in technology that has extended information fusion and dissemination from the realms of data aggregation, association and monitoring of interactions among hardware and software entities in ubiquitous computing environments to intelligent information processing for the next generation wireless internet.A distributed sensor network is a set of spatially scattered sensors that self-organize to derive appropriate inferences from the information gained in real-time. sensor fusion is thus primarily concerned with the synergistic use of information from multiple sensors by fusing across raw data, capabilities and decisions. Emerging technologies for sensing and pervasive computing have extended the scope of information fusion for distributed sensor networks from a simple merger of multiple sensor inputs to fusion of data and knowledge from multiple perspectives. For the emerging hybrid sensor networks, information fusion can assist in the seamless integration of smart sensors and actuators, devices and capabilities, software and hardware agents, sensor network applications and sensor nodes, distributed and collaborative algorithms, different communication technologies, different networking architectures, etc., in order to facilitate information networking towards timely and intelligent decision *** special issue is devoted to information fusion in the broader context of emerging sensor networks. The aim here has been to provide a focal point for recent advances in this foundational area of information fusion and dissemination, in distributed sensor networks, across different paradigms, disciplines and *** special issue includes eight papers, each of which provides a new insight on the field of information fus

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Distributed multi-sensor fusion

Distributed multi-sensor fusion

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Multisensor, Multisource Information fusion: architectures, algorithms, and applications 2008

作者： Scheffel, Peter Fish, Robert Knobler, Ron Plummer, Thomas McQ Inc. 1551 Forbes Street Fredericksburg VA 22405-1603

ISBN: (纸本)9780819471659

McQ has developed a broad based capability to fuse information in a geographic area from multiple sensors to build a better understanding of the situation. The paper will discuss the fusion architecture implemented by McQ to use many sensors and share their information. This multi sensor fusion architecture includes data sharing and analysis at the individual sensor, at communications nodes that connect many sensors together, at the system server/user interface, and across multi source information available through networked services. McQ will present a data fusion architecture that integrates a "Feature Information Base" (FIB) with McQ's well known Common Data Interchange Format (CDIF) data structure. The distributed multi sensor fusion provides enhanced situation awareness for the user.

关键词： Information fusion

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Image fusion: algorithms and applications illustrated edition

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2008年

作者： Tania Stathaki

ISBN: (纸本)9780123725295;0123725291

The application of sensor technology has brought considerable interest in the area of image fusion. Written by leading experts in the field, this book brings together in one volume the most recent algorithms, design techniques and applications in the topical field of image fusion. The applications are drawn from military, medical and civilian areas and give practical advice and pointers to the development of future applications in a variety of *** book will be an invaluable resource to R&D engineers, academic researchers and system developers requiring the most up-to-date and complete information on image fusion algorithms, design architectures and applications.*Brings together the latest algorithms, design techniques and applications in the hot area of Image fusion*A large number of applications from military, medical and civilian fields give practical advice on how to develop future applications.* Combines theory and practice to create a unique point of reference

关键词： Image processing Data processing. Image processing Digital techniques. Multisensor data fusion.

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Data and sensor fusion for bistatic applications

Data and sensor fusion for bistatic applications

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Conference on Multisensor, Multisource Information fusion

作者： Lee, Anne L. Walden Univ Minneapolis MN 55401 USA

ISBN: (纸本)9780819471659

Detection and tracking of sophisticated targets involving increased resolution and the utility of synthetic aperture transmitter windows require new and innovative approaches to active sensor technologies. The bistatic technique to target tracking is extended to form a multistatic radar system using multiple and separate transmitters and receivers that are designated sparsely located in a region. The fusion of the received data through the utility of a non-linear Kalman filter technique is discussed to predict track through observations from the multistatic system. Target positions and velocities are estimated and the error is shown to converge to zero. The Munkre algorithm is utilized for data and track association to improve error minimization.

关键词： Munkre algorithm resolution active sensors data fusion tracking non-linear Kalman filtering radar

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