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检索条件"任意字段=IET Conference on Data Fusion and Target Tracking 2014: Algorithms and Applications"

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data fusion for a Vision-Radiological System: a Statistical Calibration Algorithm 4

Data Fusion for a Vision-Radiological System: a Statistical ...

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4th International conference on Advancements in Nuclear Instrumentation Measurement Methods and their applications (ANIMMA)

作者： Enqvist, Andreas Koppal, Sanjeev Riley, Phillip Univ Florida Gainesville FL 32611 USA

ISBN: (纸本)9781479999187

Presented here is a fusion system based on simple, low-cost computer vision and radiological sensors for tracking of multiple objects and identifying potential radiological materials being transported or shipped. The main focus of this work is the development of calibration algorithms for characterizing the fused sensor system as a single entity. There is an apparent need for correcting for a scene deviation from the basic inverse distance-squared law governing the detection rates even when evaluating system calibration algorithms. In particular, the computer vision system enables a map of distance-dependence of the sources being tracked, to which the time-dependent radiological data can be incorporated by means of data fusion of the two sensors' output data.

关键词： Computer vision

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Context Aided Sensor and Human-based Information fusion

Context Aided Sensor and Human-based Information Fusion

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IEEE National Aerospace and Electronics conference (NAECON)

作者： Blasch, Erik US Air Force Res Lab Rome NY 13441 USA

ISBN: (纸本)9781479946891

Information fusion consists of organizing a set of data into meaningful reports to answer queries, forge a consistency story, and determine situation awareness. To provide situation understanding requires context both in information estimation and data management. In this paper, we highlight the importance of context estimation, assessment, and management to support information fusion analysis. A demonstrated example for multimodal human-based text analysis and video-based sensing and tracking is shown where context provides the basis for associating the multimodal data correlated in space and time. The use of context is demonstrated as (1) semantic text call-outs from users monitoring a video following a target for classification, (2) geographical road information from a database to locate a target, and (3) sensor-based estimation for simultaneous target tracking and classification. Context assessment and management from human-based and sensor-based sources is shown for information fusion situation awareness.

关键词： Information fusion Level 5 High-Level Information fusion context assessment context management

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Probabilistic step and turn detection in indoor localization

Probabilistic step and turn detection in indoor localization

引用

iet conference on data fusion & target tracking 2014: algorithms and applications (DF&TT 2014)

作者： Lukas Köping Marcin Grzegorzek Frank Deinzer University of Applied Sciences Würzburg-Schweinfurt Würzburg Germany Pattern Recognition Group University of Siegen Siegen Germany

ISBN: (纸本)9781632666642

. In this paper we present a method to estimate a position in buildings without using absolute positioning data like WiFi signals. Unlike other state-of-the-art methods, we use probability estimations for possible steps and 90° turns. The only information source we use is the data collected by a smartphone's accelerometer and gyroscope and the floor map information. The current position is tracked with the help of particle filtering. For this, we integrate the information of the previous state into the weight update step. In addition we show how the observation data can help within the state transition model.

关键词： State Change observational data Information source Steps Smartphone Particle filters Wi-Fi Gyroscopes Turning Probability absolute location Buildings Current Position information

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Visualization of Graphical Information fusion Results

Visualization of Graphical Information Fusion Results

引用

conference on Signal Processing, Sensor/Information fusion, and target Recognition XXIII

作者： Blasch, Erik Lechuck, Georgiy Staskevich, Gennady Burke, Dustin Aved, Alex Air Force Res Lab Informat Directorate Rome NY 13441 USA Aptima Woburn MA 01801 USA

ISBN: (纸本)9781628410280

Graphical fusion methods are popular to describe distributed sensor applications such as target tracking and pattern recognition. Additional graphical methods include network analysis for social, communications, and sensor management. With the growing availability of various data modalities, graphical fusion methods are widely used to combine data from multiple sensors and modalities. To better understand the usefulness of graph fusion approaches, we address visualization to increase user comprehension of multi-modal data. The paper demonstrates a use case that combines graphs from text reports and target tracks to associate events and activities of interest visualization for testing Measures of Performance (MOP) and Measures of Effectiveness (MOE). The analysis includes the presentation of the separate graphs and then graph-fusion visualization for linking network graphs for tracking and classification.

关键词： Graphical Information fusion Metrics Analysis

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Fusing Kinect sensor and inertial sensors with multi-rate Kalman filter

Fusing Kinect sensor and inertial sensors with multi-rate Ka...

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iet conference on data fusion & target tracking 2014: algorithms and applications (DF&TT 2014)

作者： Shimin Feng Roderick Murray-Smith School of Computing Science University of Glasgow Glasgow UK

ISBN: (纸本)9781632666642

This paper presents a sensor fusion approach to fusing Microsoft Kinect sensor and the built-in inertial sensors in a mobile device. A multi-rate Kalman filter is designed and applied for fusing the low-sampling-rate (30Hz) uncertain positions sensed by the Kinect sensor and the high-sampling-rate (90Hz) accelerations measured by the inertial sensors. These sensors have complementary properties. The Kinect can be applied for skeleton tracking, which gives the joints' positions. Meanwhile, the built-in inertial sensors in the mobile device sense the hand motion and the acceleration can be estimated through inertial sensor fusion. Firstly, convert the acceleration estimated with inertial sensors from the body frame into the Kinect coordinate system. Experimental results show that the hand accelerations estimated with the Kinect sensor and the inertial sensors are comparable. Secondly, design and apply a multi-rate Kalman filter for sensor fusion. The sensor fusion helps improve the accuracy of the system state estimation including the position, the velocity and the acceleration. This is of great benefit for combining inertial sensors and the external position sensing device for indoor augmented reality (AR) and other location-aware sensing applications.

关键词： inertia sensor Sensor fusion game player acceleration body frame State estimation Kalman filters Sensors

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Distributed data fusion Algorithm for Wireless Sensor Network

Distributed Data Fusion Algorithm for Wireless Sensor Networ...

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IEEE 11th International conference on Networking, Sensing and Control (ICNSC)

作者： Abdelgawad, A. Cent Michigan Univ Sch Engn & Technol Mt Pleasant MI 48859 USA

ISBN: (纸本)9781479931064

Signal processing in Wireless Sensor Network (WSN) has a huge range of applications. Distributed Kalman Filter (DKF) is one of the most fundamental distributed estimation algorithms for scalable wireless sensor fusion. DKF finds applications in object tracking, environmental monitoring, surveillance, and many other applications. All algorithms proposed in the literature are based on static network. In reality, the network topology is changing. The topology change is often caused by node failure, which is due to energy depletion. In this work a DKF is proposed for such network. The simulation and the experimental results validate our proposed DKF. The experimental results show that each sensor node can run DKF with up to six neighbors.

关键词： Distributed Kalman Filter Digital Signal Processing Wireless Sensor Network

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PHD filtering in presence of highly structured sea clutter process and tracks with extent

PHD filtering in presence of highly structured sea clutter p...

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iet conference on data fusion & target tracking 2014: algorithms and applications (DF&TT 2014)

作者： Amadou Gning Simon J. Julier Jordi Barr John Anderson Dave Miller Mark L. Williams Computer Science University College London UK Advanced Technology Centre BAE Systems UK BAE Systems Maritime Services UK

ISBN: (纸本)9781632666642

Multitarget tracking is fundamental in many security and surveillance applications. However, as algorithms have been applied in more and more challenging environments, traditional simplifications no longer even approximately hold true. In particular, we consider the problem of maritime surveillance in which small targets (boats) are to be detected and tracked in the presence of highly structured noise (waves). In particular, we consider two problems. The first is that, given the resolution of modern radar systems, even small targets are extended, straddling multiple range or azimuth bins. The second is that sea clutter is not a uniform, Poisson-distributed noise process but is highly spatially varying. In this paper, we develop two extensions of the Probability Hypothesis Density (PHD) Filter. Using a generalised likelihood model, extended targets can be readily accounted for. Through the use of spatially varying clutter models, structured noise approximation is provided. The algorithms were developed and tested using a sea trial in which Rigid-Hulled Inflatable Boats (RHIBs), equipped with GPS receivers, were tracked using a radar system.

关键词： Random Finite Set Finite Set Statistics Sequential Monte Carlo Techniques Sea clutter Sea clutter Radar systems Ship trials structured noise algorithms multiple target tracking GPS Receiver clutter presences azimuth

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Decentralised road-map assisted ground target tracking using a team of UAVs

Decentralised road-map assisted ground target tracking using...

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9th iet data fusion & target tracking conference (DF&TT 2012): algorithms & applications

作者： Hyondong Oh Seungkeun Kim Antonios Tsourdos Brian White Department of Informatics and Systems Engineering Cranfield University Defence Academy of the United Kingdom Swindon UK Department of Aerospace Engineering Chungnam National University Daejeon South Korea

ISBN: (纸本)9781622761951

This paper presents a ground moving target tracking filter and guidance using a team of UAVs. To improve the estimation accuracy, approximated road-map information using constant curvature segments is utilised with a constrained filtering. Furthermore, the decentralised extended information filter and the Kalman consensus algorithm are applied to a standoff orbit tracking problem along with coordinated vector field guidance, and their performances are analysed depending on the communication noises and network structures using a realistic car trajectory data.

关键词： target tracking Constrained filtering Decentralised estimation Communication structure noise(communication) Decentralized Web filters ground NETWORK STRUCTURE Guidance targets tracking mapping information target tracking

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A fast multi-target tracking algorithm based on local track association for multi-static radar

A fast multi-target tracking algorithm based on local track ...

引用

International conference on Microwave and Millimeter Wave Technology

作者： Wu, Yaoyun Luo, Feiteng Chen, Weidong Univ Sci & Technol China Dept Elect Engn & Informat Sci Hefei 230027 Peoples R China

ISBN: (纸本)9781424418794

A fast multi-target tracking algorithm is presented for T-R-N (one transmitter and N receivers) radar system in which only range-sum and velocity-sum can be observed. After preprocessing to initialize one-dimensional local track for each target, a novel hypothesis testing with velocity-sum is employed to eliminate false tracks caused by localization procedure. Then, the fusion center realizes multi-target tracking by using local track association technique instead of complex data association of "measurements-to-measurements" and "measurements-to-track". Compared with centralized tracking methods, this algorithm is much easier and simpler to apply in engineering, so is suitable for real-time applications.

关键词： Clutter (information theory)

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Real-time Multi-target tracking at 210 Megapixels/second in Wide Area Motion Imagery

Real-time Multi-Target Tracking at 210 Megapixels/second in ...

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IEEE Winter conference on applications of Computer Vision (WACV)

作者： Basharat, Arslan Turek, Matt Xu, Yiliang Atkins, Chuck Stoup, David Fieldhouse, Keith Tunison, Paul Hoogs, Anthony Kitware Inc Clifton Pk NY 12065 USA

ISBN: (纸本)9781479949854

We present a real-time, full-frame, multi-target Wide Area Motion Imagery (WAMI) tracking system that utilizes distributed processing to handle high data rates while maintaining high track quality. The proposed architecture processes the WAMI data as a series of geospatial tiles and implements both process- and thread-level parallelism across multiple compute nodes. Each tile is processed independently, from decoding the image through generating tracks that are finally merged across all tiles by an inter-tile linker (ITL) module. A high performance PostgreSQL database with GIS extensions is used to control the flow of intermediate data between each tracking process. High quality tracks are produced efficiently due to robust, effective algorithmic modules including: multi-frame moving object detection and track initialization;tracking based on the fusion of motion and appearance with a goal of very pure tracks;and online track linking based on multiple features. In addition, we have configured a high-performance compute cluster using high density blade servers, Infiniband networking, and an HPC filesystem. The compute cluster enables full-frame, state-of-the-art tracking of vehicles or dismounts at the WAMI sensor's native 1.25Hz frame-rate, while only taking 7u of rack space and providing 210 megapixels/second throughput.

关键词： Object detection

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