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检索条件"任意字段=Conference on Geospatial Informatics, Fusion, and Motion Video Analytics V"

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Semantically enabled image similarity search 5

Semantically enabled image similarity search

引用

conference on geospatial informatics, fusion, and motion video analytics v

作者： Casterline, May v. Emerick, Timothy Sadeghi, Kolia Gosse, C. Alec Bartlett, Brent Casey, Jason Commonwealth Comp Res Inc Charlottesville VA 22901 USA Eidetic Technol LLC Washington DC USA

ISBN: (纸本)9781628415896

Georeferenced data of various modalities are increasingly available for intelligence and commercial use, however effectively exploiting these sources demands a unified data space capable of capturing the unique contribution of each input. This work presents a suite of software tools for representing geospatial vector data and overhead imagery in a shared high-dimension vector or "embedding" space that supports fused learning and similarity search across dissimilar modalities. While the approach is suitable for fusing arbitrary input types, including free text, the present work exploits the obvious but computationally difficult relationship between GIS and overhead imagery. GIS is comprised of temporally-smoothed but information-limited content of a GIS, while overhead imagery provides an information-rich but temporally-limited perspective. This processing framework includes some important extensions of concepts in literature but, more critically, presents a means to accomplish them as a unified framework at scale on commodity cloud architectures.

关键词： Image Search Semantic Embedding Model fusion Distributed Computing geospatial Context Knowledge graph

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Cueing motion blur for registration of inclined planar scenes 5

Cueing motion blur for registration of inclined planar scene...

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conference on geospatial informatics, fusion, and motion video analytics v

作者： Nair, Arun Asokan Rao, M. Purnachandra Rajagopalan, A. N. Seetharaman, Guna Indian Inst Technol Dept Elect Engn Madras 600036 Tamil Nadu India AFRL RIEA Informat Directorate Rome NY USA

ISBN: (纸本)9781628415896

Existing image registration methods that work in the presence of motion blur assume the scene to be fronto-parallel. In this work, we extend the state-of-the-art by cueing motion blur itself to infer plane inclination. This is achieved by matching extremities of blur kernels computed at different locations in the image. Because these extremities correspond to the same homography, we show that it is possible to find the orientation. Following this, we propose a registration method that reorients the source image to the target plane within a reblur-difference framework to detect the actual changes.

关键词： Image registration occlusion detection normal estimation motion blur aerial imagery

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Addressing Fundamental Architectural Challenges of an Activity Based Intelligence and Advanced analytics (ABIAA) System 5

Addressing Fundamental Architectural Challenges of an Activi...

引用

conference on geospatial informatics, fusion, and motion video analytics v

作者： Yager, Kevin Albert, Thomas Brower, Bernard v. Pellechia, Matthew F. Exelis Inc Rochester NY 14606 USA

ISBN: (纸本)9781628415896

The domain of geospatial Intelligence Analysis is rapidly shifting toward a new paradigm of Activity Based Intelligence (ABI) and information-based Tipping and Cueing. General requirements for an advanced ABIAA system present significant challenges in architectural design, computing resources, data volumes, workflow efficiency, data mining and analysis algorithms, and database structures. These sophisticated ABI software systems must include advanced algorithms that automatically flag activities of interest in less time and within larger data volumes than can be processed by human analysts. In doing this, they must also maintain the geospatial accuracy necessary for cross-correlation of multi-intelligence data sources. Historically, serial architectural workflows have been employed in ABIAA system design for tasking, collection, processing, exploitation, and dissemination. These simpler architectures may produce implementations that solve short term requirements;however, they have serious limitations that preclude them from being used effectively in an automated ABIAA system with multiple data sources. This paper discusses modern ABIAA architectural considerations providing an overview of an advanced ABIAA system and comparisons to legacy systems. It concludes with a recommended strategy and incremental approach to the research, development, and construction of a fully automated ABIAA system.

关键词： GEOINT geospatial architecture imaging workflow analytics activity based intelligence

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AESOP: Adaptive Event detection SOftware using Programming by example 5

AESOP: Adaptive Event detection SOftware using Programming b...

引用

conference on geospatial informatics, fusion, and motion video analytics v

作者： Thangali, Ashwin Prasad, Harsha Kethamakka, Sai Demirdjian, David Checka, Neal Vecna Technol Inc 36 Cambridge Pk Dr Cambridge MA 02140 USA

ISBN: (纸本)9781628415896

This paper presents AESOP, a software tool for automatic event detection in video. AESOP employs a supervised learning approach for constructing event models, given training examples from different event classes. A trajectory-based formulation is used for modeling events with an aim towards incorporating invariance to changes in the camera location and orientation parameters. The proposed formulation is designed to accommodate events that involve interactions between two or more entities over an extended period of time. AESOP's event models are formulated as HMMs to improve the event detection algorithm's robustness to noise in input data and to achieve computationally efficient algorithms for event model training and event detection. AESOP's performance is demonstrated on a wide range of different scenarios, including stationary camera surveillance and aerial video footage captured in land and maritime environments.

关键词： Full motion video event detection supervised event model training trajectory based event models probabilistic event modeling using HMMs persistent tracking multi-target tracking

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Geo Mesa: a distributed architecture for spatio-temporal fusion 5

Geo Mesa: a distributed architecture for spatio-temporal fus...

引用

conference on geospatial informatics, fusion, and motion video analytics v

作者： Hughes, James N. Annex, Andrew Eichelberger, Christopher N. Fox, Anthony Hulbert, Andrew Ronquest, Michael Commonwealth Comp Res Inc Charlottesville VA 22901 USA

ISBN: (纸本)9781628415896

Recent advances in distributed databases and computing have transformed the landscape of spatio-temporal machine learning. This paper presents GeoMesa, a distributed spatio-temporal database built on top of Hadoop and column-family databases such as Accumulo and HBase, that includes a suite of tools for indexing, managing and analyzing both vector and raster data. The indexing techniques use space filling curves to map multidimensional data to the single lexicographic list managed by the underlying distributed database. In contrast to traditional non-distributed RDBMS, GeoMesa is capable of scaling horizontally by adding more resources at runtime;the index rebalances across the additional resources. In the raster domain, GeoMesa leverages Accumulo's server-side iterators and aggregators to perform raster interpolation and associative map algebra operations in parallel at query time. The paper concludes with two geo-time data fusion examples: using GeoMesa to aggregate Twitter data by keywords;and georegistration to drape full-motion video (FMv) over terrain.

关键词： distributed computing distributed databases Accumulo NoSQL Geohash Space Filling Curve GeoMesa spatio-temporal fusion

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Information fusion Performance Evaluation for motion Imagery Data using Mutual Information (initial study) 5

Information Fusion Performance Evaluation for Motion Imagery...

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conference on geospatial informatics, fusion, and motion video analytics v

作者： Grieggs, Samuel M. McLaughlin, Michael J. Ezekiel, Soundararajan Blasch, Erik Indiana Univ Penn Indiana PA 15701 USA Air Force Res Lab Rome NY 13441 USA

ISBN: (纸本)9781628415896

As technology and internet use grows at an exponential rate, video and imagery data is becoming increasingly important. various techniques such as Wide Area motion imagery (WAMI), Full motion video (FMv), and Hyperspectral Imaging (HSI) are used to collect motion data and extract relevant information. Detecting and identifying a particular object in imagery data is an important step in understanding visual imagery, such as content-based image retrieval (CBIR). Imagery data is segmented and automatically analyzed and stored in dynamic and robust database. In our system, we seek utilize image fusion methods which require quality metrics. Many Image fusion (IF) algorithms have been proposed based on different, but only a few metrics, used to evaluate the performance of these algorithms. In this paper, we seek a robust, objective metric to evaluate the performance of IF algorithms which compares the outcome of a given algorithm to ground truth and reports several types of errors. Given the ground truth of a motion imagery data, it will compute detection failure, false alarm, precision and recall metrics, background and foreground regions statistics, as well as split and merge of foreground regions. Using the Structural Similarity Index (SSIM), Mutual Information (MI), and entropy metrics;experimental results demonstrate the effectiveness of the proposed methodology for object detection, activity exploitation, and CBIR.

关键词： Image fusion Edge Detection Mutual Information Entropy Structural Similarity

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Geostatistical modeling of uncertainty, simulation, and proposed applications in GIScience 5

Geostatistical modeling of uncertainty, simulation, and prop...

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conference on geospatial informatics, fusion, and motion video analytics v

作者： Doucette, Peter Dolloff, John Lenihan, Michael Nat Geospatial Intelligence Agency Springfield VA 22150 USA

ISBN: (纸本)9781628415896

Geostatistical modeling of spatial uncertainty has its roots in the mining, water and oil reservoir exploration communities, and has great potential for broader applications as proposed in this paper. This paper describes the underlying statistical models and their use in both the estimation of quantities of interest and the Monte-Carlo simulation of their uncertainty or errors, including their variance or expected magnitude and their spatial correlations or inter-relationships. These quantities can include 2D or 3D terrain locations, feature vertex locations, or any specified attributes whose statistical properties vary spatially. The simulation of spatial uncertainty or errors is a practical and powerful tool for understanding the effects of error propagation in complex systems. This paper describes various simulation techniques and trades-off their generality with complexity and speed. One technique recently proposed by the authors, Fast Sequential Simulation, has the ability to simulate tens of millions of errors with specifiable variance and spatial correlations in a few seconds on a lap-top computer. This ability allows for the timely evaluation of resultant output errors or the performance of a "down-stream" module or application. It also allows for near-real time evaluation when such a simulation capability is built into the application itself.

关键词： error covariance matrix variogram spatial correlation Monte Carlo Fast Sequential Simulation

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Full motion video Geopositioning Algorithm Integrated Test Bed 5

Full Motion Video Geopositioning Algorithm Integrated Test B...

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conference on geospatial informatics, fusion, and motion video analytics v

作者： Dolloff, John Hottel, Bryant Doucette, Peter Braun, Aaron Theiss, Henry Gurson, Adam Natl Geospatial Intelligence Agcy Springfield VA 22150 USA

ISBN: (纸本)9781628415896

In order to better understand the issues associated with Full motion video (FMv) geopositioning and to develop corresponding strategies and algorithms, an integrated test bed is required. It is used to evaluate the performance of various candidate algorithms associated with registration of the video frames and subsequent geopositioning using the registered frames. Major issues include reliable error propagation or predicted solution accuracy, optimal vs. suboptimal vs. divergent solutions, robust processing in the presence of poor or non-existent a priori estimates of sensor metadata, difficulty in the measurement of tie points between adjacent frames, poor imaging geometry including small field-of-view and little vertical relief, and no control (points). The test bed modules must be integrated with appropriate data flows between them. The test bed must also ingest/generate real and simulated data and support evaluation of corresponding performance based on module-internal metrics as well as comparisons to real or simulated "ground truth". Selection of the appropriate modules and algorithms must be both operator specifiable and specifiable as automatic. An FMv test bed has been developed and continues to be improved with the above characteristics. The paper describes its overall design as well as key underlying algorithms, including a recent update to "A matrix" generation, which allows for the computation of arbitrary inter-frame error cross-covariance matrices associated with Kalman filter (KF) registration in the presence of dynamic state vector definition, necessary for rigorous error propagation when the contents/definition of the KF state vector changes due to added/dropped tie points. Performance of a tested scenario is also presented.

关键词： full motion video registration error propagation accuracy prediction multi-image geopositioning

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Real-time automated detection, tracking, classification, and geolocation of dismounts using EO and IR FMv 5

Real-time automated detection, tracking, classification, and...

引用

conference on geospatial informatics, fusion, and motion video analytics v

作者： Muncaster, J. Collins, G. Waltman, J. Toyon Res Corp Goleta CA 93117 USA

ISBN: (纸本)9781628415896

The videoPlus (R)-Aware (vPA) system enables autonomous video-based target detection, tracking and classification. The system stabilizes video and operates completely autonomously. A statistical background model enables robust acquisition of moving targets, while stopped targets are tracked using feature-based detectors. An ensemble classifier is trained for automated detection and classification of dismounts (i.e., humans) and a planar scene model is used to both improve system performance and reduce false positives. A formal evaluation of the vPA system was performed by the government, to quantify the system's abilities to detect, track, and classify, humans. The evaluation provided 811 separate data points gathered over a period of four days with an overall probability of sensing of 99.9%. The probability of detection was 86.2% and the percentage of correct action classification was 82%. The data provided a False Alarm Rate of 0 per hour and Nuisance Alarm Rate of 0.72 per hour. Dismounts were reliably classified with pixel heights as low as 25 pixels. Real-time automated detection, tracking, and classification of targets with low false positive rates was achieved, even with few pixels on target. The planar scene model based optimizations were sufficient to dramatically reduce the runtime of sliding-window classifiers.

关键词： Automated Detection Tracking Classification video Surveillance video analytics Automation

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Smart phone orientation estimation comparisons using three axis gimbal 6

Smart phone orientation estimation comparisons using three a...

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conference on geospatial informatics, fusion, and motion video analytics vI

作者： Gaquin, Kevin G. Fields, MaryAnne Engility Corp Bldg 1121B Aberdeen Proving Ground MD 21005 USA Army Res Lab Bldg 1120 Aberdeen Proving Ground MD USA

ISBN: (纸本)9781510600829

Smartphones have put powerful sensor arrays in nearly everyone's pockets. Fusing the data from these sensors it is possible to estimate the phone's current orientation. In this study we utilize a 3 axis gimbal to compare the performance of multiple orientation estimation algorithms. Controlling the position of the gimbal allows us to compare the known device orientation to the estimated orientation. Using this same method we determine where each algorithm's faults lie, and where they begin to break down. Then repeating these movements we are able to compare each algorithm to each other.

关键词： Smartphone Attitude Estimation Sensor fusion Orientation Estimation Activity Classification Comparison Gimbal MARG

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