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Human cognitive and perceptual factors in JDL level 4 hard / soft data fusion

Proceedings of SPIE - The International Society for Optical Engineering 2012年 8407卷

作者： Rimland, Jeffrey C. Hall, David L. Graham, Jacob L. Pennsylvania State University College of Information Sciences and Technology 101 IST Building University Park PA 16802-6822 United States

ISBN: (纸本)9780819490858

Utilization of human participants as "soft sensors" is becoming increasingly important for gathering information related to a wide range of phenomena including natural and man-made disasters, environmental changes over time, crime prevention, and other roles of the "citizen scientist." The ubiquity of advanced mobile devices is facilitating the role of humans as "hybrid sensor platforms", allowing them to gather data (e.g. video, still images, GPS coordinates), annotate it based on their intuitive human understanding, and upload it using existing infrastructure and social networks. However, this new paradigm presents many challenges related to source characterization, effective tasking, and utilization of massive quantities of physical sensor, human-based, and hybrid hard/soft data in a manner that facilitates decision making instead of simply amplifying information overload. In the Joint Directors of Laboratories (JDL) data fusion process model, "level 4" fusion is a meta-process that attempts to improve performance of the entire fusion system through effective source utilization. While there are well-defined approaches for tasking and categorizing physical sensors, these methods fall short when attempting to effectively utilize a hybrid group of physical sensors and human observers. While physical sensor characterization can rely on statistical models of performance (e.g. accuracy, reliability, specificity, etc.) under given conditions, "soft" sensors add the additional challenges of characterizing human performance, tasking without inducing bias, and effectively balancing strengths and weaknesses of both human and physical sensors. This paper addresses the challenges of the evolving human-centric fusion paradigm and presents cognitive, perceptual, and other human factors that help to understand, categorize, and augment the roles and capabilities of humans as observers in hybrid systems. © 2012 SPIE.

关键词： Data fusion

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Agent-based analysis of trustworthiness in wireless sensor networks

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Proceedings of SPIE - The International Society for Optical Engineering 2012年 8407卷

作者： Fernandes, Ronald Li, Biyan Vadakkeveedu, Kalyan Verma, Ajay Gustafson, Paul Hwang, Jong Knowledge Based Systems Inc. 1408 University Drive East College Station TX77840 United States Air Force Research Lab at Wright Patterson Air Force Base Dayton OH 45433 United States

ISBN: (纸本)9780819490858

Information assurance is a critical component of any organization's data network. Trustworthiness of the sensor data, especially in the case of wireless sensor networks (WSNs), is an important metric for any application that requires situational awareness. In a WSN, information packets are typically not encrypted and the nodes themselves could be located in the open, leaving them susceptible to tampering and physical degradation. In order to develop a method to assess trustworthiness in WSNs, we have utilized statistical trustworthiness metrics and have implemented an agentbased simulation platform that can perform various trustworthiness measurement experiments for various WSN operating scenarios. Different trust metrics are used against multiple vulnerabilities to detect anomalous behavior and node failure as well as malicious attacks. The simulation platform simulates WSNs with various topologies, routing algorithms, battery and power consumption models, and various types of attacks and defense mechanisms. Additionally, we adopt information entropy based techniques to detect anomalous behavior. Finally, detection techniques are fused to provide various metrics, and various trustworthiness metrics are fused to provide aggregate trustworthiness for the purpose of situational awareness. © 2012 SPIE.

关键词： Network security

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Allothetic and idiothetic sensor fusion in rat-inspired robot localization

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Proceedings of SPIE - The International Society for Optical Engineering 2012年 8407卷

作者： Weitzenfeld, Alfredo Fellous, Jean-Marc Barrera, Alejandra Tejera, Gonzalo Div. of Information Technology University of South Florida Polytechnic 3433 Winter Lake Rd Lakeland FL 33803 United States Dept. of Psychology and Applied Mathematics University of Arizona 1503 E University Blvd. Tucson AZ 85721 United States Dept. of Computer Engineering Instituto Tecnológico Autónomo de México Rio Hondo #1 Mexico DF 01080 Mexico Inst. of Comp. Julio Herrera y Reissig 565 Universidad de la República Montevideo 11300 Uruguay

ISBN: (纸本)9780819490858

We describe a spatial cognition model based on the rat's brain neurophysiology as a basis for new robotic navigation architectures. The model integrates allothetic (external visual landmarks) and idiothetic (internal kinesthetic information) cues to train either rat or robot to learn a path enabling it to reach a goal from multiple starting positions. It stands in contrast to most robotic architectures based on SLAM, where a map of the environment is built to provide probabilistic localization information computed from robot odometry and landmark perception. Allothetic cues suffer in general from perceptual ambiguity when trying to distinguish between places with equivalent visual patterns, while idiothetic cues suffer from imprecise motions and limited memory recalls. We experiment with both types of cues in different maze configurations by training rats and robots to find the goal starting from a fixed location, and then testing them to reach the same target from new starting locations. We show that the robot, after having pre-explored a maze, can find a goal with improved efficiency, and is able to (1) learn the correct route to reach the goal, (2) recognize places already visited, and (3) exploit allothetic and idiothetic cues to improve on its performance. We finally contrast our biologically-inspired approach to more traditional robotic approaches and discuss current work in progress. © 2012 SPIE.

关键词： Robots

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Advances in data representation for hard/soft information fusion

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Proceedings of SPIE - The International Society for Optical Engineering 2012年 8407卷

作者： Rimland, Jeffrey C. Coughlin, Dan Hall, David L. Graham, Jacob L. Pennsylvania State University College of IST 101IST Building University Park PA 16802-6822 United States Pennsylvania State University OE03 Paterno Library University Park PA 16802 United States

ISBN: (纸本)9780819490858

Information fusion is becoming increasingly human-centric. While past systems typically relegated humans to the role of analyzing a finished fusion product, current systems are exploring the role of humans as integral elements in a modular and extensible distributed framework where many tasks can be accomplished by either human or machine performers. For example, "participatory sensing" campaigns give humans the role of "soft sensors" by uploading their direct observations or as "soft sensor platforms" by using mobile devices to record human-annotated, GPS-encoded high quality photographs, video, or audio. Additionally, the role of "human-in-the-loop", in which individuals or teams using advanced human computer interface (HCI) tools such as stereoscopic 3D visualization, haptic interfaces, or aural "sonification" interfaces can help to effectively engage the innate human capability to perform pattern matching, anomaly identification, and semantic-based contextual reasoning to interpret an evolving situation. The Pennsylvania State University is participating in a Multi-disciplinary University Research Initiative (MURI) program funded by the U.S. Army Research Office to investigate fusion of hard and soft data in counterinsurgency (COIN) situations. In addition to the importance of this research for Intelligence Preparation of the Battlefield (IPB), many of the same challenges and techniques apply to health and medical informatics, crisis management, crowd-sourced "citizen science", and monitoring environmental concerns. One of the key challenges that we have encountered is the development of data formats, protocols, and methodologies to establish an information architecture and framework for the effective capture, representation, transmission, and storage of the vastly heterogeneous data and accompanying metadata -- including capabilities and characteristics of human observers, uncertainty of human observations, "soft" contextual data, and information pedigree. This

关键词： Service oriented architecture (SOA)

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Plenary talk IV: Robust 3-D vision techniques: algorithms and applications

Plenary talk IV: Robust 3-D vision techniques: Algorithms an...

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SICE Annual Conference

作者： In So Kweon KAIST South Korea

Summary form only given: For the 3D reconstruction of static and dynamic scenes, we have developed several robust computer vision methods ranging from the image enhancement to the design of novel camera systems. In this talk, we first present a sparse-model based approach to recover the camera response function, which is crucial for many color image processing problems such as high dynamic range imaging and photo-consistent mosaicking. We also present a sensor-fusion based approach to obtain super-resolution (SR) depth images from low-resolution depth images and high-resolution color images. A learning-based optimization framework successfully recovers the SR depth images. The second part of the talk introduces new camera systems to capture the 3D information accurately and efficiently. The camera systems include (i) “camera + depth” fusion camera systems, (ii) a fast bundle adjustment based approach for large-scale datasets, (iii) a novel coded-light photometric stereo for modeling 3-D dynamic scenes. Specifically, we present a hand-held fusion sensor system, consisting of four cameras and two 2D laser scanners, to capture 3D information of large-scale scenes. This new approach allows boosting the advantages of two sensor systems and complements the weakness of the two. As an important application of 3D vision techniques, we demonstrate the robustness of the methods by automatically reconstructing a large-scale environment, such as KAIST campus.

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Smart Environmental Architecture for Node Localization in a Wireless sensor Network

Smart Environmental Architecture for Node Localization in a ...

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International Conference on Intelligent Environments (IE)

作者： Salvador Jauregui-Ortiz Mario Siller Felix Ramos Edson Scalabrin Electrical Engineering and Computer Science Department Center of Research and Advanced Studies of the IPN Guadalajara Jalisco Mexico Graduate Program in Computer Science Pontifical Catholic University Parana Brazil Curitiba Parana Brazil

As far as we know, there is not a Node Localization Algorithm (NLA) that presents the same accuracy for all possible scenarios. We believe that a NLA should be able to "interpret" the dynamic information of the environment. In this sense, simple NLAs are rather focused and might perform well for specific scenarios and applications. Therefore, information fusion and context awareness seems to be an appropriate approach to address this issue. We propose the Smart Environmental Architecture for Node Localization (SEA-NL), which is composed by two main elements: (i) the Smart Beacon Nodes (SBNs) and (ii) the Logical Position of Nodes (LPN). In (i) the obstruction level indicator is estimated and can improve the estimation of distances among nodes. In (ii) environment information and a one to one relation between a node and an object are used and can also improve location estimation. Via simulation, our architecture was tested indoors and outdoors considering three localization algorithms: the Weighed Centroid Localization (WCL), the Centroid Localization, and the Triangular Centroid Localization. Finally, we present an accuracy comparison among NLAs used in isolated way, and by using the SBNs, the LPN, and the SEA-NL, where our architecture improves WCL up to ~30.88%.

关键词： Wireless sensor networks Accuracy Estimation Computer architecture Buildings Attenuation Monitoring

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architectures, algorithms, and applications Using Bayesian Networks

Architectures, Algorithms, and Applications Using Bayesian N...

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

作者： Kingsbury, Todd Gen Dynam Adv Informat Syst San Diego CA 92108 USA

ISBN: (纸本)9780819486387

A Bayesian network is a tree structure where each branch represents a classification candidate. The leaves of the tree represent observable target features such as frequency or length. An optimized tree groups similar features together, e.g. frequency and pulse width, while collecting dissimilar or disparate information, e. g. spectral and kinematics, all within the same unifying structure. A vehicular track then is a subset of the a priori candidate library and contains only feasible branches. The algorithm for updating the confidence of each feasible candidate according to Bayes' rule is embedded in each track, as is the ability of a track to learn, apply a priori probability distributions, switch modes, switch among kinematics models, apply tracking history to classification and apply classification history to tracking, and support multisensor correlation and sensor fusion.

关键词： Bayesian tracking classification sensor fusion

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Implementation and testing of a sensor-netting algorithm for early warning and high confidence C/B threat detection

Implementation and testing of a sensor-netting algorithm for...

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

作者： Gruber, Thomas Grim, Larry Fauth, Ryan Tercha, Brian Powell, Chris Steinhardt, Kristin MESH Inc Oxford PA 19363 USA

ISBN: (纸本)9780819486387

Large networks of disparate chemical/biological (C/B) sensors, MET sensors, and intelligence, surveillance, and reconnaissance (ISR) sensors reporting to various command/display locations can lead to conflicting threat information, questions of alarm confidence, and a confused situational awareness. sensor netting algorithms (SNA) are being developed to resolve these conflicts and to report high confidence consensus threat map data products on a common operating picture (COP) display. A data fusion algorithm design was completed in a Phase I SBIR effort and development continues in the Phase ii SBIR effort. The initial implementation and testing of the algorithm has produced some performance results. The algorithm accepts point and/or standoff sensor data, and event detection data (e. g., the location of an explosion) from various ISR sensors (e.g., acoustic, infrared cameras, etc.). These input data are preprocessed to assign estimated uncertainty to each incoming piece of data. The data are then sent to a weighted tomography process to obtain a consensus threat map, including estimated threat concentration level uncertainty. The threat map is then tested for consistency and the overall confidence for the map result is estimated. The map and confidence results are displayed on a COP. The benefits of a modular implementation of the algorithm and comparisons of fused /un-fused data results will be presented. The metrics for judging the sensor-netting algorithm performance are warning time, threat map accuracy (as compared to ground truth), false alarm rate, and false alarm rate v. reported threat confidence level.

关键词： sensor netting algorithm fusion tomography map uncertainty consistency

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The Continuum fusion theory of signal detection applied to a bi-modal fusion problem

The Continuum Fusion theory of signal detection applied to a...

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

作者： Schaum, A. USN Res Lab Washington DC 20375 USA

ISBN: (纸本)9780819486387

A new formalism has been developed that produces detection algorithms for model-based problems, in which one or more parameter values is unknown. Continuum fusion can be used to generate different flavors of algorithm for any composite hypothesis testing problem. The methodology is defined by a fusion logic that can be translated into max/min conditions. Here it is applied to a simple sensor fusion model, but one for which the generalized likelihood ratio test is intractable. By contrast, a fusion-based response to the same problem can be devised that is solvable in closed form and represents a good approximation to the GLR test.

关键词： bi-modal continuum fusion detector algorithm

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A Constraint Sufficient Statistics based Distributed Particle Filter for Bearing Only Tracking

A Constraint Sufficient Statistics based Distributed Particl...

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IEEE International Conference on Communications

作者： Arash Mohammadi Amir Asif Computer Science and Engineering York University

ISBN: (纸本)9781457720529

A constrained sufficient statistic based distributed implementation of the particle filter (CSS/DPF) is proposed for angle/bearing-only tracking (BOT) applications. The CSS/DPF runs localized particle filters at each sensor node and computes the global sufficient statistics (GSS) of the overall system as a function (summation) of the local sufficient statistics (LSS). The CSS/DPF is, therefore, a two stage procedure: (i) First, the means of LSS at local nodes are computed by running average consensus algorithms to derive the GSS, and;(ii) Each node then updates its localized particle filter using the modified GSS. Simulation results show that the CSS/DPF is near-optimal with its performance almost identical to that of the centralized particle filter. The number of average consensus runs in the CSS/DPF are reduced by an order of magnitude of the dimension of the state vector, thereby, reducing the communication complexity and bandwidth requirement of the distributed implementation.

关键词： Consensus Algorithm Data fusion Distributed Estimation Bearing-only Tracking Particle Filters Particle filters Aerospace ground services PRNP gene communication complexity LSS gene bandwidth requirement Sufficient Distribute dimensions

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