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检索条件"任意字段=Conference on Sensor Fusion - Architectures, Algorithms, and Applications"

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Generalized Information fusion and Visualization Using Spatial Voting and Data Modeling

Generalized Information Fusion and Visualization Using Spati...

引用

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

作者： Jaenisch, Holger M. Handley, James W. SPIE Bellingham WA 98227 USA Licht Strahl Engn INC Toney AL 35773 USA Johns Hopkins Univ Baltimore MD 21218 USA

ISBN: (纸本)9780819495471

We present a novel and innovative information fusion and visualization framework for multi-source intelligence (multiINT) data using Spatial Voting (SV) and Data Modeling. We describe how different sources of information can be converted into numerical form for further processing downstream, followed by a short description of how this information can be fused using the SV grid. As an illustrative example, we show the modeling of cyberspace as cyber layers for the purpose of tracking cyber personas. Finally we describe a path ahead for creating interactive agile networks through defender customized Cyber-cubes for network configuration and attack visualization.

关键词： Spatial Voting Data Modeling Information fusion Agile networks Cyber defense Cyber Persona Tracking

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sensor and System for Measuring Oculomotor Activity

Sensor and System for Measuring Oculomotor Activity

引用

conference on Signal Processing - algorithms, architectures, Arrangements, and applications (SPA)

作者： Murawski, Krzysztof Rozanowski, Krzysztof Sondej, Tadeusz Truszczynski, Olaf Mil Univ Technol Kaliskiego Str 2 PL-00908 Warsaw Poland Mil Inst Aviat Med P-01755 Warsaw Poland

ISBN: (纸本)9788362065172

The paper presents the designed active non-contact optical sensor, as well as the system for measuring oculomotor activity. Oculomotor activity is examined in order to determine the fatigue level of the driver. In the created system, fatigue is detected by analyzing variability of the signals obtained in real-time: percentage of eyelid closure/opening, blink frequency, activity of the eyes and pupil diameter. The presented system has been successfully tested in simulated and live environment in changeable weather and lighting conditions.

关键词： Eye-Tracking Oculomotor Activity Fatigue

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Leaf recognition and segmentation by using depth image

Leaf recognition and segmentation by using depth image

引用

International conference on Agro-Geoinformatics

作者： Xiaowei Shao Yun Shi Wenbing Wu Peng Yang Zhongxin Chen Ryosuke Shibasaki Earth Observation Data Integration and Fusion Research Initiative University of Tokyo Tokyo Japan Institute of Agricultural Resources and Regional Planning Chinese Academy of Agricultural Sciences Beijing China Center for Spatial Information Science University of Tokyo Tokyo Japan

Measuring the geometric structural traits of plants, especially the shape of leaves, plays an important role in the agricultural science. However, most existing techniques and systems have limited overall performance in accuracy, efficiency and descriptive ability, which is insufficient for the requirements in many real applications. In this study, a new kind of sensing device, the Kinect depth sensor which measures the real distance to objects directly and is able to capture high-resolution depth images, is exploited for the automatic recognition and extraction of leaves. The pixels of the depth image are converted into a set of 3D points and transformed into a standard coordinate system after ground calibration. Leaves are extracted based on the height information and a hierarchical clustering algorithm, which combines the density-based spatial clustering algorithm and the mean-shift algorithm, is proposed for the automatic segmentation of leaves. Experimental result shows the effectiveness of our proposed method.

关键词： Three-dimensional displays Calibration Clustering algorithms Shape sensors Image segmentation Image color analysis

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fusion of Data from Multiple sensors with Model-Based Data Analysis

Fusion of Data from Multiple Sensors with Model-Based Data A...

引用

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

作者： Straub, Jeremy Univ North Dakota Dept Comp Sci 3950 Campus RdStop 9015 Grand Forks ND 58202 USA

ISBN: (纸本)9780819495471

For many applications, the combination of multiple data sources is required to reach a conclusion. Limited communications and processing capabilities dictate transmitting, processing and reviewing information more likely to affect a decision before less relevant data. Autonomous craft must, thus, prioritize data for transmission, onboard. Previous work demonstrated the ability to identify and prioritize discrepancies between collected and pre-existing image, topographic and gravitational data. This paper focuses on combining single-source analysis from these datasets to produce a fusion-analysis for predicting the decision-impact value of the component data. This approach is evaluated for persistent surveillance and asteroid assessment applications.

关键词： model-based transmission reduction multiple data source fusion prioritization of data for transmission link budget maximization link budget reduction

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Multi-brain fusion and applications to intelligence analysis

Multi-brain fusion and applications to intelligence analysis

引用

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

作者： Stoica, A. Matran-Fernandez, A. Andreou, D. Poli, R. Cinel, C. Iwashita, Y. Padgett, C. NASA Jet Prop Lab Pasadena CA USA

ISBN: (纸本)9780819495471

In a rapid serial visual presentation (RSVP) images are shown at an extremely rapid pace. Yet, the images can still be parsed by the visual system to some extent. In fact, the detection of specific targets in a stream of pictures triggers a characteristic electroencephalography (EEG) response that can be recognized by a brain-computer interface (BCI) and exploited for automatic target detection. Research funded by DARPA's Neurotechnology for Intelligence Analysts program has achieved speed-ups in sifting through satellite images when adopting this approach. This paper extends the use of BCI technology from individual analysts to collaborative BCIs. We show that the integration of information in EEGs collected from multiple operators results in performance improvements compared to the single-operator case.

关键词： Bain-Computer Interfaces collaborative BCI Rapid Serial Visual Presentation visual search

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Spatial Voting For Automatic Feature Selection, fusion, and Visualization

Spatial Voting For Automatic Feature Selection, Fusion, and ...

引用

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

作者： Jaenisch, Holger Handley, James Licht Strahl Engineering Inc. (United States) Johns Hopkins Univ. (United States) Alabama A&M Univ. (United States)

ISBN: (纸本)9780819495471

We present a novel feature selection, fusion, and visualization utility using Spatial Voting (SV). This SV feature optimization utility is designed to be an off-line stand-alone utility to help an investigator find useful feature pairs for cluster analysis and lineage identification. The analysis can be used to enable the analyst to vary parameters manually and explore the best combination that yields visually appealing or significant groups or spreading of data points depending on the planned use of the analysis downstream. Several different criteria are available to the user in order to determine the best SV grid size and feature pair including minimizing zeros, minimizing covariance, balanced minimum covariance, or the maximization of one of eight different scoring metrics: Containment, Rand Index, Purity, Precision, Recall, F-Score, Normalized Mutual Information (NMI), and Adjusted Rand Index (ARI). The tool that is described in this work facilitates this analysis and makes it simple, efficient, and interactive if the analyst so desires.

关键词： Spatial Voting Automatic Feature Selection fusion Visualization NMI Rand Index ARI

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Vehicle Model based Outlier Detection for Automotive Visual Odometry

Vehicle Model based Outlier Detection for Automotive Visual ...

引用

conference on Signal Processing - algorithms, architectures, Arrangements, and applications (SPA)

作者： Ohr, Florian M. Parakrama, Thusitha Rosenstiel, W. Univ Tubingen Fac Sci D-72076 Tubingen Germany Chassis Syst Control Robert Bosch GmbH D-71229 Leonberg Germany

ISBN: (纸本)9788362065172

In this paper we present a novel outlier detection scheme for image feature based ego-motion estimation in automotive applications. It is based on a restrictive motion model, describing the relationship between road vehicle motion and camera motion. The model also enables the integration of ESP sensor data, such as measured longitudinal velocity and yaw-rate. In this way a high precision camera motion prediction is realized, which is used to identify erroneous feature correspondences. High costs of standard methods like the iterative random sample consensus (RANSAC) [1] are thereby avoided.

关键词： Vehicle model image feature outliers Automotive applications odometry Standard Methods automotive engineering Cameras road vehicles DNA Integration integration

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Performance Analysis of Image fusion Methods in Transform Domain

Performance Analysis of Image Fusion Methods in Transform Do...

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

作者： Choi, Yoonsuk Sharifahmadian, Ershad Latifi, Shahram Univ Nevada Dept Elect & Comp Engn 4505 Maryland Pkwy Las Vegas NV 89154 USA

ISBN: (纸本)9780819495471

Image fusion involves merging two or more images in such a way as to retain the most desirable characteristics of each. There are various image fusion methods and they can be classified into three main categories: i) Spatial domain, ii) Transform domain, and iii) Statistical domain. We focus on the transform domain in this paper as spatial domain methods are primitive and statistical domain methods suffer from a significant increase of computational complexity. In the field of image fusion, performance analysis is important since the evaluation result gives valuable information which can be utilized in various applications, such as military, medical imaging, remote sensing, and so on. In this paper, we analyze and compare the performance of fusion methods based on four different transforms: i) wavelet transform, ii) curvelet transform, iii) contourlet transform and iv) nonsubsampled contourlet transform. fusion framework and scheme are explained in detail, and two different sets of images are used in our experiments. Furthermore, various performance evaluation metrics are adopted to quantitatively analyze the fusion results. The comparison results show that the nonsubsampled contourlet transform method performs better than the other three methods. During the experiments, we also found out that the decomposition level of 3 showed the best fusion performance, and decomposition levels beyond level-3 did not significantly affect the fusion results.

关键词： Curvelet contourlet decomposition nonsubsampled contourlet wavelet

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Affordable Non-Traditional Source Data Mining for Context Assessment to Improve Distributed fusion System Robustness

Affordable Non-Traditional Source Data Mining for Context As...

引用

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

作者： Bowman, Christopher Haith, Gary Data Fusion & Neural Networks LLC (United States) Georgia Tech Research Institute (United States) Arctan Group LLC (United States)

ISBN: (纸本)9780819495471

This paper describes methods to affordably improve the robustness of distributed fusion systems by opportunistically leveraging non-traditional data sources. Adaptive methods help find relevant data, create models, and characterize the model quality. These methods also can measure the conformity of this non-traditional data with fusion system products including situation modeling and mission impact prediction. Non-traditional data can improve the quantity, quality, availability, timeliness, and diversity of the baseline fusion system sources and therefore can improve prediction and estimation accuracy and robustness at all levels of fusion. Techniques are described that automatically learn to characterize and search non-traditional contextual data to enable operators integrate the data with the high-level fusion systems and ontologies. These techniques apply the extension of the Data fusion & Resource Management Dual Node Network (DNN) technical architecture at Level 4. The DNN architecture supports effectively assessment and management of the expanded portfolio of data sources, entities of interest, models, and algorithms including data pattern discovery and context conformity. Affordable model-driven and data-driven data mining methods to discover unknown models from non-traditional and 'big data' sources are used to automatically learn entity behaviors and correlations with fusion products, [14 and 15]. This paper describes our context assessment software development, and the demonstration of context assessment of non-traditional data to compare to an intelligence surveillance and reconnaissance fusion product based upon an IED POIs workflow.

关键词： Data fusion Data modeling sensors Systems modeling Intelligence systems Data processing Performance modeling Control systems Data acquisition Data mining

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Bayesian Approach to Multisensor Data fusion with Pre- and Post-Filtering

Bayesian Approach to Multisensor Data Fusion with Pre- and P...

引用

10th IEEE International conference on Networking, Sensing and Control (ICNSC)

作者： Abdulhafiz, Waleed A. Khamis, Alaa Siemens Low & Medium Voltage Div Cairo Egypt Suez Univ Engn Sci Dept Fac Petr & Mining Engn Suez Egypt

ISBN: (纸本)9781467352000;9781467351980

Data provided by sensors is always affected by some level of uncertainty or lack of certainty in the measurements. Combining data from several sources using multisensor data fusion algorithms exploits the data redundancy to reduce this uncertainty. This paper proposes an approach to multisensor data fusion that relies on combining a modified Bayesian fusion algorithm with Kalman filtering. Three different approaches namely: Pre-Filtering, Post-Filtering and Pre-Post-Filtering are described based on how filtering is applied to the sensor data, to the fused data or both. A case study of estimating the position of a mobile robot using optical encoder and Hall-effect sensor is presented. Experimental study shows that combining fusion with filtering helps in handling the problem of uncertainty and inconsistency of the data in both centralized and decentralized data fusion architectures.

关键词： Multisensor data fusion Bayesian approach Kalman filtering mobile robot positioning

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