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检索条件"任意字段=Sensor Fusion: Architectures, Algorithms and Applications II"

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Information fusion and uncertainty management for biological multisensor systems

Information fusion and uncertainty management for biological...

引用

Conference on Multisensor, Multisource Information fusion

作者： Braun, JJ Glina, Y Stein, DW Skomoroch, PN Fox, EB MIT Lincoln Lab Lexington MA 02420 USA

ISBN: (纸本)0819457981

This paper investigates methods of decision-making from uncertain and disparate data. The need for such methods arises in those sensing application areas in which multiple and diverse sensing modalities are available, but the information provided can be imprecise or only indirectly related to the effects to be discerned. Biological sensing for biodefense is an important instance of such applications. Information fusion in that context is the focus of a research program now underway at MIT Lincoln Laboratory. The paper outlines a multi-level, multi-classifier recognition architecture developed within this program, and discusses its components. Information source uncertainty is quantified and exploited for improving the quality of data that constitute the input to the classification processes. Several methods of sensor uncertainty exploitation at the feature-level are proposed and their efficacy is investigated. Other aspects of the program are discussed as well. While the primary focus of the paper is on biodefense, the applicability of concepts and techniques presented here extends to other multisensor fusion application domains.

关键词： information fusion multisensor data fusion machine learning biological sensors biodefense

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Image fusion with the hybrid evolutionary algorithm and response analysis

Image fusion with the hybrid evolutionary algorithm and resp...

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Conference on Multisensor, Multisource Information fusion

作者： Maslov, IV CUNY Dept Comp Sci Grad Ctr New York NY 10016 USA

ISBN: (纸本)0819457981

Information fusion is a rapidly developing research area aimed at creating methods and tools capable of augmenting security and defense systems with the state-of-the-art computational power and intelligence. An important part of information fusion, image fusion serves as the basis for a fully automatic object and target recognition. Image fusion maps images of the same scene received from different sensors into a common reference system. Using sensors of different types gives rise to a problem of finding a set of invariant features that help overrun the imagery difference caused by the different types of sensors. The paper describes an image fusion method based on the combination of the hybrid evolutionary algorithm and image local response. The latter is defined as an image transform R(V) that maps an image into itself after a geometric transformation A(V) defined by a parameter vector V is applied to the image. The transform R(V) identifies the dynamic content of the image, i.e. the salient features that are most responsive to the geometric transformation A(V). Moreover, since R(V) maps the image into itself, the result of the mapping is largely invariant to the type of the sensor used to obtain the image. Image fusion is stated as the global optimization problem of finding a proper transformation A(V) that minimizes the difference between the images subject to fusion. Hybrid evolutionary algorithm can be applied to solving the problem. Since the search for the optimal parameter vector V is conducted in the response space rather than in the actual image space, the differences in the sensor types can be significantly alleviated.

关键词： information fusion image fusion target recognition optimization hybrid evolutionary algorithm response analysis

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Advances in low-power visible/thermal IR video image fusion hardware

Advances in low-power visible/thermal IR video image fusion ...

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Conference on Thermosense XXVii

作者： Wolff, LB Socolinsky, DA Eveland, CK Equinox Corp New York NY 10019 USA

ISBN: (纸本)0819457671

Equinox Corporation has developed two new video board products for real-time image fusion of visible (or intensified visible/near-infrared) and thermal (emissive) infrared video. These products can provide unique capabilities to the dismounted soldier, maritime/naval operations and Unmanned Aerial Vehicles (UAVs) with low-power, lightweight, compact and inexpensive FPGA video fusion hardware. For several years Equinox Corporation has been studying and developing image fusion methodologies using the complementary modalities of the visible and thermal infrared wavebands including applications to face recognition, tracking, sensor development and fused image visualization. The video board products incorporate Equinox's proprietary image fusion algorithms into an FPGA architecture with embedded programmable capability. Currently included are (i) user interactive image fusion algorithms that go significantly beyond standard "A+B" fusion providing an intuitive color visualization invariant to distracting illumination changes, (ii) generalized image co-registration to compensate for parallax, scale and rotation differences between visible/intensified and thermal IR, as well as non-linear optical and display distortion, and (iii) automatic gain control (AGC) for dynamic range adaptation.

关键词： Image fusion Thermography Infrared imaging Visible radiation Infrared radiation Video Cameras Infrared cameras Visualization Image visualization

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Real time implementation of image alignment and fusion

Real time implementation of image alignment and fusion

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Conference on Multisensor, Multisource Information fusion

作者： Dwyer, D Smith, M Dale, J Heather, J Octec Ltd Western Ctr Bracknell RG12 1RW Berks England

ISBN: (纸本)0819457981

Many modern imaging and surveillance systems contain more than one sensor. For example, most modern airborne imaging pods contain at least visible and infrared sensors. Often these systems have a single display that is only capable of showing data from either camera, and thereby fail to exploit the benefit of having simultaneous multi-spectral data available to the user. It can be advantageous to capture all spectral features within each image and to display a fused result rather than single band imagery. This paper discusses the key processes necessary for an image fusion system and then describes how they were implemented in a real-time, rugged hardware system. The problems of temporal and spatial misalignment of the sensors and the process of electronic image warping must be solved before the image data is fused. The techniques used to align the two inputs to the fusion system are described and a summary is given of our research into automatic alignment techniques. The benefits of different image fusion schemes are discussed and those that were implemented are described. The paper concludes with a summary of the real-time implementation of image alignment and image fusion by Octec and Waterfall Solutions and the problems that have been encountered and overcome.

关键词： image alignment image fusion real time image processing

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Prior knowledge integration of road dependant ground target behaviour for improving tracking reliability

Prior knowledge integration of road dependant ground target ...

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Conference on Multisensor, Multisource Information fusion

作者： Gattein, S Vannoorenberghe, P Contat, M EADS S&DE Voie Future F-27106 Val De Reuil France

ISBN: (纸本)0819457981

This paper describes an algorithm for tracking ground targets, mainly based on measurements from a MTI radar. We examine the use of prior knowledge on target type for automatically improving the performance of a purely kinematic tracker. This tracker is an adaptation from a Variable Structure Interacting Multiple Model (VS-IMM) estimator acting within an S-Dimensional Assignment method. The algorithm can thus track several targets with false alarms, and the variable structure allows to use only the relevant dynamic models relative to roads in the vicinity of the target's prediction. However the sets of possible on-road and off-road models do not interact as in the usual IMM mechanism. Instead the on-road behaviour of a target across S-I radar scans is optimally managed in a hypothesis tree, since we do not mix incompatible road models. However, both global on-road and off-road behaviours are handled by mode transition probabilities, making it possible to track targets that change their behaviour regarding the road network with the same algorithm. Next an automatic measured type data integration scheme is examined, that can be connected to the above kinematic framework. The incoming measured type data is modelled by a belief function to reflect uncertainty, as well as the sensor's reliability. Simulation results show the operation of the kinematic tracker for road targets, illustrating the relevance of the variable structure dynamic model set.

关键词： data fusion target tracking VS-MM S-D assignment belief function

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Multi-sensor, multi-source information fusion: Architecture, algorithms, and applications - A panoramic overview

Multi-sensor, multi-source information fusion: Architecture,...

引用

ICCC 2004 - Second IEEE International Conference on Computational Cybernetics

作者： Dasarathy, Belur V.

ISBN: (纸本)0780385888

This plenary presentation offers a panoramic overview of the field of multi-sensor, and/or multi-source information fusion from three complementary perspectives, namely, architectures, algorithms, and applications. This overview is developed through addressing the questions of 'what', 'why', 'when', and last but not least 'how' of information fusion and illustrating the answers with appropriate algorithmic and applicative examples. © 2004 IEEE.

关键词： sensor data fusion

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sensor management and Bayesian networks

Sensor management and Bayesian networks

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Conference on Multisensor, Multisource Information fusion

作者： Yilmazer, N Osadciw, LA Syracuse Univ Dept Elect Engn & Comp Sci Syracuse NY 13244 USA

ISBN: (纸本)0819453579

This paper introduces the sensor management problem and uses Bayesian networks as a scalable approach to handling the operational decisions concerning the sensor network. In general, single sensor systems only provide partial information on the state of the event or environment while multisensor systems provide a synergistic effect, which improves the quality and availability of information. Data fusion techniques can effectively combine this environmental information from similar and/or dissimilar sensors. Until recently, the operator could manage the systems easily, but current systems are more complex and produce data more quickly than earlier versions. A sensor manager becomes necessary when this occurs to assist the operators. Researchers have developed many single point sensor management solutions. General sensor management algorithms that can handle a variety of sensor network applications have yet to emerge.

关键词： sensor management Bayesian networks fusion

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Real time sensor validation and fusion for distributed autonomous sensors

Real time sensor validation and fusion for distributed auton...

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Conference on Multisensor, Multisource Information fusion

作者： Yuan, XJ Li, XS Buckles, B Tulane Univ EECS Dept New Orleans LA 70118 USA

ISBN: (纸本)0819453579

Multi-sensor data fusion has found widespread applications in industrial and research sectors. The purpose of real time multi-sensor data fusion is to dynamically estimate an improved system model from a set of different data sources, i.e., sensors. This paper presented a systematic and unified real time sensor validation and fusion framework (RTSVFF) based on distributed autonomous sensors. The RTSVFF is an open architecture which consists of four layers - the transaction layer, the process fusion layer, the control layer, and the planning layer. This paradigm facilitates distribution of intelligence to the sensor level and sharing of information among sensors, controllers, and other devices in the system. The openness of the architecture also provides a platform to test different sensor validation and fusion algorithms and thus facilitates the selection of near optimal algorithms for specific sensor fusion application. In the version of the model presented in this paper, confidence weighted averaging is employed to address the dynamic system state issue noted above. The state is computed using an adaptive estimator and dynamic validation curve for numeric data fusion and a robust diagnostic map for decision level qualitative fusion. The framework is then applied to automatic monitoring of a gas-turbine engine, including a performance comparison of the proposed real-time sensor fusion algorithms and a traditional numerical weighted average.

关键词： real time sensor validation and fusion distributed sensor system design dynamic validation curve file based knowledge system confidence weighted averaging robust diagnostic maps

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Cognitive engineering in algorithm development for multisensor data fusion in military applications

Cognitive engineering in algorithm development for multisens...

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Conference on Multisensor, Multisource Information fusion

作者： Kight, AC Narayanan, S Wright State Univ Dept Biomed Ind & Human Factors Engn Dayton OH 45435 USA

ISBN: (纸本)0819453579

In battlefield situations, human operators are bombarded with substantial amounts of information and expected to make near-instantaneous decisions. The large amounts of information, coupled with short decision times and the need to reduce the potential of making incorrect decisions, create the possibility for information overload. This problem is especially prominent in military applications involving imagery from multiple sensors. Computer-based algorithms for fusing pertinent sets of imagery have proven somewhat useful for alleviating this problem. However, little research has been done on designing multisensor data fusion systems using principles of cognitive engineering, which involves the consideration of human cognition during the design process. The design of a sensor fusion system using principles from cognitive engineering would create a more natural relationship between human and machine, and would thus be extremely effective in reducing operator error in military situations. This paper explores the need for integrating human reasoning and cognition in algorithm development for multisensor fusion applications.

关键词： Algorithm development Data fusion Defense technologies Cognition Image fusion Error analysis Image sensors sensor fusion sensors

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A scalable, portable, object-oriented framework for parallel multi-sensor data-fusion applications in HPC systems

A scalable, portable, object-oriented framework for parallel...

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Conference on Multisensor, Multisource Information fusion

作者： Gupta, P Prasad, G Univ Cent Florida Sch Comp Sci Orlando FL 32816 USA

ISBN: (纸本)0819453579

Multi-sensor Data fusion is synergistic integration of multiple data sets. Data fusion includes processes for aligning, associating and combining data and information in estimating and predicting the state of objects, their relationships, and characterizing situations and their significance. The combination of complex data sets and the need for real-time data storage and retrieval compounds the data fusion problem. The systematic development and use of data fusion techniques are particularly critical in applications requiring massive, diverse, ambiguous, and time-critical data. Such conditions are characteristic of new emerging requirements;e.g., network-centric and information-centric warfare, low intensity conflicts such as special operations, counter narcotics, antiterrorism, information operations and CALOW (Conventional Arms, Limited Objectives Warfare), economic and political intelligence. In this paper, Aximetric presents a novel, scalable, object-oriented, metamodel framework for parallel, cluster-based data-fusion engine on High Performance Computing (HPC) Systems. The data-clustering algorithms provide a fast, scalable technique to sift through massive, complex data sets coming through multiple streams in real-time. The load-balancing algorithm provides the capability to evenly distribute the workload among processors on-the-fly and achieve real-time scalability. The proposed data-fusion engine exploits unique data-structures for fast storage, retrieval and interactive visualization of the multiple data streams.

关键词： sensor fusion HPC systems meta-modefing object-oriented simulation data fusion

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