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Multi-sensor detection and fusion technique

Multi-sensor detection and fusion technique

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conference on Multisensor, Multisource Information fusion

作者： Bhargave, Ashish Arnbrose, Barry Lin, Freddie Kazantzidis, Manthos Broadata Commun Inc Torrance CA USA

ISBN: (纸本)9780819466938

A multi-sensor detection and fusion technology is described in this paper. The system consist of inputs from three sensors, Infra Red, Doppler Motion, and Stereo Video. This choice of sensors is designed to give high reliability, infra red and Doppler to provide detection ability at night, stereo video has the ability to analyze depth and range information. The combination of these sensors has the ability to provide high probability of detection and very low false alarm rate. The technique consists of three processing parts corresponding to each sensor data, and a fusion module, which makes the final decision based on the inputs from the three parts. The signal processing and detection algorithms process the inputs from each sensors and provides a specific information to the fusion module. fusion module is based on bayes belief propagation theory. It takes the processed inputs from all the sensor modules and provides a final decision on the presence and absense of objects, as well as their reliability based on the iterative belief propagation algorithm operating on decision graphs. A prototype system was built using the technique to study the feasibility of intrusion detection for NASA's launch danger zone protection. The system verified the potential of the proposed algorithms and proved the feasibility of high probability of detection and low false alarm rates compared to many existing techniques.

关键词： sensors Video Detection and tracking algorithms Image processing Doppler effect Prototyping Signal processing Infrared sensors Surveillance Video surveillance

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Automated image registration using the projective transformation model and block matching feature point pair selection

Automated image registration using the projective transforma...

引用

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

作者： Schultz, RR Alford, MG Univ N Dakota Dept Elect Engn Grand Forks ND 58202 USA

ISBN: (纸本)0819431931

A subpixel-resolution image registration algorithm based on the nonlinear projective transformation model is proposed to account for camera translation, rotation, zoom, pan, and tilt. Typically, parameter estimation techniques for rigid-body transformations require the user to manually select feature point pairs between the images undergoing registration. In this research, the block matching algorithm is used to automatically select correlated feature point pairs between two images;these features are then used to calculate an iterative least squares estimate of the nonlinear projective transformation parameters. Since block matching is only capable of estimating accurate displacement vectors in image regions containing a large number of edges, inaccurate feature point pairs are statistically eliminated prior to computing the least squares parameter estimate. Convergence of the registration algorithm is generally achieved in several iterations. Simulations show that the algorithm estimates accurate integer- and subpixel-resolution registration parameters for similar sensor data sets such as intensity image sequence fi ames, as well as for dissimilar sensor images such as multimodality slices from the Visible Human Project. Through subpixel-resolution registration, integrating the registered pixels fi om a short sequence of low-resolution video fi-ames generates a high-resolution video still. Experimental results are also shown in utilizing dissimilar data registration followed by vector quantization to segment tissues from multimodality Visible Human Project image slices.

关键词： block matching image registration projective transformation sensor fusion super-resolution enhancement

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Real-time EO/IR sensor fusion on a portable computer and head mounted display

Real-time EO/IR sensor fusion on a portable computer and hea...

引用

conference on Multisensor, Multisource Information fusion

作者： Yue, Zhanfeng Topiwala, Pankaj LLC FastVDO 7150 Riverwood Dr Columbia MD 21046 USA

ISBN: (纸本)9780819466938

Multi-sensor platforms are widely used in surveillance video systems for both military and civilian applications. The complimentary nature of different types of sensors (e.g. EO and IR sensors) makes it possible to observe the scene under almost any condition (day/night/fog/smoke). In this paper, we propose an innovative EO/IR sensor registration and fusion algorithm which runs real-time on a portable computing unit with head-mounted display. The EO/IR sensor suite is mounted on a helmet for a dismounted soldier and the fused scene is shown in the goggle display upon the processing on a portable computing unit. The linear homography transformation between images from the two sensors is pre-computed for the mid-to-far scene, which reduces the computational cost for the online calibration of the sensors. The system is implemented in a highly optimized C++ code, with MMX/SSE, and performing a real-time registration. The experimental results on real captured video show the system works very well both in speed and in performance.

关键词： real-time sensor fusion homography

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Taking advantage of misclassifications to boost classification rate in decision fusion

Taking advantage of misclassifications to boost classificati...

引用

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

作者： Goebel, K Mysore, SP GE Corp Res & Dev Niskayuna NY 12309 USA

ISBN: (纸本)0819440809

This paper presents methods to boost the classification rate in decision fusion with partially redundant information. This is accomplished by utilizing the information of known misclassifications of certain classes to systematically modify class output. For example, if it is known beforehand that tool A misclassifies class 1 often as class 2, then it appears to be prudent to integrate that information into the reasoning process if class 1 is indicated by tool B and class 2 is observed by tool A. Particularly this preferred misclassification information is contained in the asymmetric (cross-correlation) entries of the confusion matrix. An operation we call "cross-correlation" is performed where this information is explicitly used to modify class output before the first fused estimate is calculated. We investigate several methods for cross-correlation and discuss the advantages and disadvantages of each. We then apply the concepts introduced to the diagnostic realm where we aggregate the output of several different diagnostic tools. We show how the proposed approach fits into an information fusion architecture and finally present results motivated from diagnosing on-board faults in aircraft engines.

关键词： classification diagnostics information fusion decision fusion correlation cross-correlation

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Colour-the-INSight: combining a direct view rifle sight with fused intensified and thermal imagery

Colour-the-INSight: combining a direct view rifle sight with...

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

作者： Hogervorst, M. A. Jansen, C. Toet, A. Bijl, P. Bakker, P. Hiddema, A. C. van Vliet, S. F. TNO Human Factors POB 23 NL-3769 GZ Soesterberg Netherlands Thales Netherland BV Huizen Netherlands Photonis Netherlands BV NL-9300 AB Groningen Netherlands Minist Def Joint Soldier & Equipment Ctr Expertise The Hague Netherlands

ISBN: (纸本)9780819490858

We present the design and evaluation of a new demonstrator rifle sight viewing system containing direct view, red aim point and fusion of an (uncooled, LWIR) thermal sensor with a digital image intensifier. Our goal is to create a system that performs well under a wide variety of (weather) conditions during daytime and nighttime and combines the advantages of the various sensor systems. A real-time colour image with salient hot targets is obtained from the night vision sensors by implementing the Colour-the-Night fusion method (Hogervorst & Toet, 2010) on the on-board processor. The prototype system was evaluated in a series of field trials with military observers performing detection and identification tasks. The tests showed that during daytime the addition of a thermal image to direct vision is advantageous, e. g. for the detection of hot targets. At nighttime, the fusion of thermal and image intensified imagery results in increased situational awareness and improved detection of (hot) targets. For identification of small (handheld) objects, the technology needs to be further refined

关键词： image fusion false colour natural colour mapping real-time fusion night vision

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Image processing, radiological, and clinical information fusion in breast cancer detection

Image processing, radiological, and clinical information fus...

引用

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

作者： Alto, H Rangayyan, RM Solaiman, B Desautels, JEL MacGregor, JH Univ Calgary Dept Elect & Comp Engn Calgary AB T2N 1N4 Canada

ISBN: (纸本)0819444812

Screening mammography is the most efficient and cost-effective method available for detecting the signs of early breast cancer in asymptomatic women between the ages of 50 and 69. To improve the detection rate and reduce the number of unnecessary biopsies, many different computer-aided diagnosis techniques have been developed(15,26). Many, of these techniques use image processing algorithms to automatically segment and classify the images. The decision-making process associated with the evaluation of mammograms is complex and incorporates multiple sources of information from standard medical knowledge and radiology to pathology. The use of this information combined with the results of image processing offers new challenges to the field of data and information fusion. In this paper, we describe the different information sources and their data as well as the framework that is needed to support this type of fusion. A database of breast cancer screening cases forms the basis of the resulting fusion model. The database and decision-level fusion techniques will facilitate unique and specialized approaches for efficient and sophisticated diagnosis of breast cancer.

关键词： Breast cancer Image processing Databases Mammography Information fusion Breast Data fusion Cancer Image fusion Image segmentation

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Scalable sensor management for automated fusion and tactical reconnaissance

Scalable sensor management for automated fusion and tactical...

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

作者： Walls, Thomas J. Wilson, Michael L. Partridge, Darin C. Haws, Jonathan R. Jensen, Mark D. Johnson, Troy R. Petersen, Brad D. Sullivan, Stephanie W. Naval Res Lab 4555 Overlook Ave SW Washington DC 20375 USA

ISBN: (纸本)9780819495471

The capabilities of tactical intelligence, surveillance, and reconnaissance (ISR) payloads are expanding from single sensor imagers to integrated systems-of-systems architectures. Increasingly, these systems-of-systems include multiple sensing modalities that can act as force multipliers for the intelligence analyst. Currently, the separate sensing modalities operate largely independent of one another, providing a selection of operating modes but not an integrated intelligence product. We describe here a sensor Management System (SMS) designed to provide a small, compact processing unit capable of managing multiple collaborative sensor systems on-board an aircraft. Its purpose is to increase sensor cooperation and collaboration to achieve intelligent data collection and exploitation. The SMS architecture is designed to be largely sensor and data agnostic and provide flexible networked access for both data providers and data consumers. It supports pre-planned and ad-hoc missions, with provisions for on-demand tasking and updates from users connected via data links. Management of sensors and user agents takes place over standard network protocols such that any number and combination of sensors and user agents, either on the local network or connected via data link, can register with the SMS at any time during the mission. The SMS provides control over sensor data collection to handle logging and routing of data products to subscribing user agents. It also supports the addition of algorithmic data processing agents for feature/target extraction and provides for subsequent cueing from one sensor to another. The SMS architecture was designed to scale from a small UAV carrying a limited number of payloads to an aircraft carrying a large number of payloads. The SMS system is STANAG 4575 compliant as a removable memory module (RMM) and can act as a vehicle specific module (VSM) to provide STANAG 4586 compliance (level-3 interoperability) to a non-compliant sensor system. Th

关键词： multi-INT data fusion sensing modality sensor management network sensor tasking automation algorithmic processing scalable systems-of-systems

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Tracking moving acoustic sources with a network of sensors

Tracking moving acoustic sources with a network of sensors

引用

conference on Unattended Ground sensor Technologies and applications iv

作者： Kozick, RJ Sadler, BM Bucknell Univ Dept Elect Engn Lewisburg PA 17837 USA

ISBN: (纸本)0819444936

This paper presents issues and algorithms for the problem of source tracking with a network of aeroacoustic sensors. We study fusion of data from sensors that are widely separated, and we give particular attention to the important issues of limited communication bandwidth between sensor nodes, effects of source motion, coherence loss between signals measured at different sensors, signal bandwidth, and noise. We compare the tracking performance of various schemes, including joint (coherent) processing of all sensor data, as well as data-reduction schemes that employ distributed computation and reduced communication bandwidth with a fusion center. The key result of our analysis is a quantification of the potential gain in source tracking accuracy that is achievable with greater communication bandwidth and joint processing of sensor data. We show that the potential gain in accuracy depends critically on the scenario, as determined by the source motion parameters, signal coherence between sensors, bandwidth of the source signals, and noise level. For scenarios that admit increased accuracy with joint processing, we present a bandwidth-efficient algorithm that involves beamforming at small-aperture sensor arrays combined with time-delay estimation between widely-spaced sensor arrays.

关键词： aeroacoustic sensor arrays source localization and tracking imperfect spatial coherence decentralized signal processing data compression and fusion

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Robust fusion with reliabilities weights

Robust fusion with reliabilities weights

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

作者： Grandin, JF Marques, M THALES Airborne Syst F-78851 Elancourt France

ISBN: (纸本)0819444812

The reliability is a value of the degree of trust in a given measurement. We analyze and compare : ML (Classical Maximum Likelihood), MLE (Maximum Likelihood weighted by Entropy), MLR (Maximum Likelihood weighted by Reliability), MLRE (Maximum Likelihood weighted by Reliability and Entropy), DS (Credibility Plausibility), DSR (DS weighted by reliabilities) The analysis is based on a model of a dynamical fusion process. It is composed of three sensors, which have each it's own discriminatory capacity, reliability rate, unknown bias and measurement noise. The knowledge of uncertainties is also severely corrupted, in order to analyze the robustness of the different fusion operators. Two sensor models are used : the first type of sensor is able to estimate the probability of each elementary hypothesis (probabilistic masses), the second type of sensor delivers masses on union of elementary hypotheses (DS masses). In the second case probabilistic reasoning leads to sharing the mass abusively between elementary hypotheses. Compared to the classical ML or DS which achieves just 50% of correct classification in some experiments, DSR, MLE, MLR and MLRE reveals very good performances on all experiments (more than 80% of correct classification rate). The experiment was performed with large variations of the reliability coefficients for each sensor (from 0 to 1), and with large variations on the knowledge of these coefficients (from 0 to 0.8). All four operators reveal good robustness, but the MLR reveals to be uniformly dominant on all the experiments in the bayesian case and achieves the best mean performance under incomplete a priori information.

关键词： decisional and dynamical multi sensors fusion robustness imprecision reliability uncertainty

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Studying the complexities in distributed object tracking systems

Studying the complexities in distributed object tracking sys...

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IEEE International conference on Systems, Man and Cybernetics (SMC 03)

作者： Llinas, J SUNY Buffalo Ctr Multisource Informat Fus Dept Ind Engn Buffalo NY 14260 USA

ISBN: (纸本)0780379527

Tracking of moving objects based on multi-sensor input is a topic that has received considerable attention, and has been the subject of many papers. As web-type capabilities have emerged, along with ever-improving wireless communications capabilities, coupled with the needs of various applications to include "Network-Centric Warfare" on the part of the military, research on distributed multi-object, multi-sensor tracking has received some attention in recent years. However, the study of these distributed problems at the complete-architecture level, accounting for (among yet other factors) organizational information-sharing protocols, dynamic network topologies, mixes of stationary and moving sensors, complex object dynamics, equipment failure modes, node-specific tracking algorithms and data fusion algorithms, does not seem to have been addressed in any "holistic" way. This paper addresses these issues and describes an integrated testbed being developed at the University at Buffalo's Center for Multisource Information fusion for the empirical study of these complex architectures involving, in essence, the interconnection of multiple systems.

关键词： Distributed Tracking filtering estimation information fusion resource management

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