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检索条件"任意字段=Multisensor. Multisource Information Fusion: Architectures, Algorithms, and Applications 2003"

共 284 条记录，以下是251-260 订阅

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Distributed sensor data compression algorithm

Distributed sensor data compression algorithm

引用

Conference on multisensor. multisource information fusion

作者： Ambrose, Barry Lin, Freddie Broadata Commun Inc 2545 W 237th St Torrance CA 90505 USA

ISBN: (纸本)0819462985

Theoretically it is possible for two sensors to reliably send data at rates smaller than the sum of the necessary data rates for sending the data independently, essentially taking advantage of the correlation of sensor readings to reduce the data rate. In 200 1, Caltech researchers Michelle Effros and Qian Zhao developed new techniques for data compression code design for correlated sensor data, which were published in a paper at the 2001 Data Compression Conference (DCC 2001). These techniques take advantage of correlations between two or more closely positioned sensors in a distributed sensor network. Given two signals, X and Y, the X signal is sent using standard data compression. The goal is to design a partition tree for the Y signal. The Y signal is sent using a code based on the partition tree. At the receiving end, if ambiguity arises when using the partition tree to decode the Y signal, the X signal is used to resolve the ambiguity. We have extended this work to increase the efficiency of the code search algorithms. Our results have shown that development of a highly integrated sensor network protocol that takes advantage of a correlation in sensor readings can result in 20-30% sensor data transport cost savings. In contrast, the best possible compression using state-of-the-art compression techniques that did not take into account the correlation of the incoming data signals achieved only 9-10% compression at most. This work was sponsored by MDA, but has very widespread applicability to ad hoc sensor networks, hyperspectral imaging sensors and vehicle health monitoring sensors for space applications.

关键词： information theory data compression sensor networks

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A Java implementation of the probabilistic argumentation system for data fusion in missile defense applications

A Java implementation of the probabilistic argumentation sys...

引用

Conference on multisensor. multisource information fusion

作者： Chan, M Hansen, T Monney, PA Baker, T Lockheed Missiles & Space Co Inc Sunnyvale CA 94089 USA

ISBN: (纸本)0819453579

In missile defense target recognition applications, knowledge about the problem may be imperfect, imprecise, and incomplete. Consequently, complete probabilistic models are not available. In order to obtain robust inference results and avoid making inaccurate assumptions, the probabilistic argumentation system (PAS) is employed. In PAS, knowledge is encoded as logical rules with probabilistically weighted assumptions. These rules map directly to Dempster-Shafer belief functions, which allow for uncertainty reasoning in the absence of complete probabilistic models. The PAS can be used to compute arguments for and against hypotheses of interest, and numerical answers that quantify these arguments. These arguments can be used as explanations that describe how inference results are computed. This explanation facility can also be used to validate intelligence information, which can in turn improve inference results. This paper presents a Java implementation of the probabilistic argumentation system as well as a number of new features. A rule-based syntax is defined as a problem encoding mechanism and for Monte Carlo simulation purposes. In addition, a graphical user interface (GUI) is implemented so that users can encode the knowledge database, and visualize relationships among rules and probabilistically weighted assumptions. Furthermore, a graphical representation is used to display these rules, which in turn provides graphical explanations of the inference results. We provide examples that illustrate how classical pattern recognition problems can be solved using canonical rule sets, as well as examples that demonstrate how this new software can be used as an explanation facility to describe how the inference results are determined.

关键词： Java implementation probabilistic argumentation system data fusion rule-based inference graphical user interface

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A mathematical framework for the optimization of rejection and ROC thresholds in the fusion of correlated sensor data

A mathematical framework for the optimization of rejection a...

引用

Conference on multisensor. multisource information fusion

作者： Laine, TI Bauer, KW USAF Inst Technol Dept Operat Sci Wright Patterson AFB OH 45433 USA

ISBN: (纸本)0819453579

In pattern recognition applications, significant costs can be associated with various decision options and a minimum acceptable level of confidence is often required. Combat target identification is one example where the incorrect labeling of Targets and Non-targets incurs substantial costs: yet, these costs may be difficult to quantify. One way to increase decision confidence is through fusion of data from multiple sources or from multiple looks through time. Numerous methods have been published to determine optimal rules for the fusion of decision labels or to determine the Bayes' optimal decision if prior and posterior probabilities along with decision costs can be accurately estimated. This paper introduces a mathematical framework to optimize multiple decision thresholds subject to a decision maker's preferences. when a continuous measure of class membership is available. Decision variables may include rejection thresholds to specify non-declaration regions and ROC thresholds to explore viable trite positive and false positive Target classification rates, where the feasible space can be partially visualized by a 3D ROC surface. This methodology yields an optimal class declaration rule subject to decision maker preferences without using explicit costs associated with each type of decision. Some properties of this optimization framework are shown for Gaussian distributions representing Target and Non-target classes with various prior probabilities and correlation levels between simulated multiple sensor looks.

关键词： combat identification (CID) fusion receiver operating characteristic (ROC). 3-D ROC surface automatic taraet recosinition (ATR) performance rejection

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Vehicle tracking in UAV video using multi-spectral spatiogram models

Vehicle tracking in UAV video using multi-spectral spatiogra...

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Conference on multisensor. multisource information fusion

作者： O'Connor, N. E. Kehoe, P. O'Conaire, C. Smeaton, A. F. Dublin City Univ Ctr Digital Video Proc Dublin 9 Ireland

ISBN: (纸本)9780819471659

In this paper we present the results of applying a general purpose feature combination framework for tracking to the specific task of tracking vehicles in UAV data sets. In the fusion framework used (previously presented elsewhere(1)) vehicles' pixel-based features from multiple channels, specifically RGB and thermal IR, are split across separate individual spatiogram trackers. The use of spatiograms allows embedding of some spatial information into the models whilst also avoiding the exponential increase in computational load and memory requirements associated with the more commonly used histogram. This tracking framework is embedded in a complete system for detecting and tracking vehicles. The system first carries out pre-processing to ensure spatially and temporally aligned visible spectrum and IR data prior to tracking. Vehicle detection in the initial two frames is achieved by first compensating for camera motion, followed by frame differencing and post-processing (thresholding and size filtering) to identify vehicle regions. Each vehicle is then described by a bounding box and this is used to generate a set of spatiograms for each of the available data channels. The detected vehicle is then tracked using the spatiogram tracker framework. Results of experiments on a variety of UAV data sets indicate the promising performance of the overall system, even in the presence of significant illumination variation, partial and full occlusions and significant camera motion and focus change. Results are particularly encouraging given that we do not periodically re-initialise the detection phase and this points to the robustness of the tracking framework.

关键词： spatiogram fusion vehicle tracking UAV

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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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Biologically-inspired robust and adaptive multi-sensor fusion and active control

Biologically-inspired robust and adaptive multi-sensor fusio...

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multisensor. multisource information fusion: architectures, algorithms, and applications 2009

作者： Khosla, Deepak Dow, Paul A. Huber, David J. HRL Laboratories LLC Malibu CA United States

ISBN: (纸本)9780819476111

In this paper, we describe a method and system for robust and efficient goal-oriented active control of a machine (e.g., robot) based on processing, hierarchical spatial understanding, representation and memory of multimodal sensory inputs. This work assumes that a high-level plan or goal is known a priori or is provided by an operator interface, which translates into an overall perceptual processing strategy for the machine. Its analogy to the human brain is the download of plans and decisions from the pre-frontal cortex into various perceptual working memories as a perceptual plan that then guides the sensory data collection and processing. For example, a goal might be to look for specific colored objects in a scene while also looking for specific sound sources. This paper combines three key ideas and methods into a single closed-loop active control system. (1) Use high-level plan or goal to determine and prioritize spatial locations or waypoints (targets) in multimodal sensory space;(2) collect/store information about these spatial locations at the appropriate hierarchy and representation in a spatial working memory. This includes invariant learning of these spatial representations and how to convert between them;and (3) execute actions based on ordered retrieval of these spatial locations from hierarchical spatial working memory and using the "right" level of representation that can efficiently translate into motor actions. In its most specific form, the active control is described for a vision system (such as a pantilt-zoom camera system mounted on a robotic head and neck unit) which finds and then fixates on high saliency visual objects. We also describe the approach where the goal is to turn towards and sequentially foveate on salient multimodal cues that include both visual and auditory inputs. © 2009 SPIE.

关键词： Data handling

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Data fusion of several support vector machine breast cancer diagnostic paradigms using a GRNN oracle

Data fusion of several support vector machine breast cancer ...

引用

Conference on multisensor. multisource information fusion

作者： Land, WH Wong, L McKee, D Masters, T Anderson, F Sarvaiya, S SUNY Binghamton Binghamton NY 13902 USA

ISBN: (纸本)0819453579

Breast cancer is second to lung cancer as a tumor-related cause of death in women. For 2003, it was reported that 211,300 new cases and 39,800 deaths would occur in the US. It has been proposed that breast cancer mortality could be decreased by 25% if women in appropriate age groups were screened regularly. Currently, the preferred method for breast cancer screening is mammography, due to its widespread availability, low cost, speed, and non-invasiveness. At the same time, while mammography is sensitive to the detection of breast cancer, its positive predictive value (PPV) is low, resulting in costly, invasive biopsies that are only 15-34% likely to reveal malignancy at histologic examination. This paper explores the use of a newly designed Support Vector Machine (SVM)/Generalized Regression Neural Network (GRNN) Oracle hybrid and evaluates the hybrid's performance as an interpretive aid to radiologists. The authors demonstrate that this hybrid has the potential to (1) improve both specificity and PPV of screen film mammography at 95-100% sensitivity, and (2) consistently produce partial A(Z) values (defined as average specificity over the top 10% of the ROC curve) of greater than 30%, using a data set of similar to2500 lesions from five different hospitals and/or institutions.

关键词： computer-aided diagnosis breast cancer Support Vector Machines GRNN Oracle

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A heterogeneous sensor network simulation system with integrated terrain data for real-time target detection in 3D space

A heterogeneous sensor network simulation system with integr...

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Conference on multisensor. multisource information fusion

作者： Lin, Hong Tanner, Steve Rushing, John Graves, Sara Criswell, Evans Univ Alabama Informat Technol & Syst Ctr Huntsville AL 35899 USA

ISBN: (纸本)9780819471659

Large scale sensor networks composed of many low-cost small sensors networked together with a small number of high fidelity position sensors can provide a robust, fast and accurate air defense and warning system. The team has been developing simulations of such large networks, and is now adding terrain data in an effort to provide more realistic analysis of the approach. This work, a heterogeneous sensor network simulation system with integrated terrain data for real-time target detection in a three-dimensional environment is presented. The sensor network can be composed of large numbers of low fidelity binary and bearing-only sensors, and small numbers of high fidelity position sensors, such as radars. The binary and bearing-only sensors are randomly distributed over a large geographic region;while the position sensors are distributed evenly. The elevations of the sensors are determined through the use of DTED Level 0 dataset. The targets are located through fusing measurement information from all types of sensors modeled by the simulation. The network simulation utilizes the same search-based optimization algorithm as in our previous two-dimensional sensor network simulation with some significant modifications. The fusion algorithm is parallelized using spatial decomposition approach: the entire surveillance area is divided into small regions and each region is assigned to one compute node. Each node processes sensor measurements and terrain data only for the assigned sub region. A master process combines the information from all the compute nodes to get the overall network state. The simulation results have indicated that the distributed fusion algorithm is efficient enough so that an optimal solution can be reached before the arrival of the next sensor data with a reasonable time interval, and real-time target detection can be achieved. The simulation was performed on a Linux cluster with communication between nodes facilitated by the Message Passing Interface (

关键词： heterogeneous sensor network data fusion terrain data real-time target detection three-dimensional space

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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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Intent inference for attack aircraft through fusion

Intent inference for attack aircraft through fusion

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Conference on multisensor. multisource information fusion

作者： Ng, Gee Wah Ng, Khin Hua Yang, Rong Foo, Pek Hui DSO Natl Labs Adv Anal & Fus Lab 20 Sci Pk Dr Singapore 118230 Singapore Natl Univ Singapore Dept Computat Sci Singapore 117543 Singapore

ISBN: (纸本)0819462985

Intent inference is about analyzing the actions and activities of an adversarial force or target of interest to reach a conclusion (prediction) on its purpose. In this paper, we report one of our research works on intent inference to deter-mine the likelihood of an attack aircraft being tracked by a military surveillance system delivering its weapon. Effective intent inference will greatly enhance the defense capability of a military force in taking preemptive action against potential adversaries. It serves as early warning and assists the commander in his decision making. For an air defense system, the ability to accurately infer the likelihood of a weapon delivery by an attack aircraft is critical. It is also important for an intent inference system to be able to provide timely inference. We propose a solution based on the analysis of flight profiles for offset pop-up delivery. Simulation tests are carried out on flight profiles generated using different combinations of delivery parameters. In each simulation test, the state vectors of the tracked aircraft are updated via the application of the Interacting Multiple Model filter. Relevant variables of the filtered track (flight trajectory) are used as inputs to a Mamdani-type fuzzy inference system. The output produced by the fuzzy inference system is the inferred possibility of the tracked aircraft carrying out a pop-up delivery. We present experimental results to support our claim that the proposed solution is indeed feasible and also provides timely inference that will assist in the decision making cycle.

关键词： fusion intent inference flight profile fuzzy logic cognitive

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