Representation of activity in images using geospatial temporal graphs

Brost, Randolph; McLendon, William C.; Parekh, Ojas D.; Rintoul, Mark Daniel; Watson, Jean-Paul; Strip, David R.; Diegert, Carl

Title: Representation of activity in images using geospatial temporal graphs

Abstract

Various technologies pertaining to modeling patterns of activity observed in remote sensing images using geospatial-temporal graphs are described herein. Graphs are constructed by representing objects in remote sensing images as nodes, and connecting nodes with undirected edges representing either distance or adjacency relationships between objects and directed edges representing changes in time. Activity patterns may be discerned from the graphs by coding nodes representing persistent objects like buildings differently from nodes representing ephemeral objects like vehicles, and examining the geospatial-temporal relationships of ephemeral nodes within the graph.

Inventors:: Brost, Randolph; McLendon, III, William C.; Parekh, Ojas D.; Rintoul, Mark Daniel; Watson, Jean-Paul; Strip, David R.; Diegert, Carl

Issue Date:: 2018-05-01

Research Org.:: Sandia National Laboratories (SNL), Albuquerque, NM, and Livermore, CA (United States)

Sponsoring Org.:: USDOE

OSTI Identifier:: 1438449

Patent Number(s):: 9959647

Application Number:: 14/848,165

Assignee:: National Technology & Engineering Solutions of Sandia, LLC (Albuquerque, NM)

Patent Classifications (CPCs):: G - PHYSICS G06 - COMPUTING G06T - IMAGE DATA PROCESSING OR GENERATION, IN GENERAL

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G - PHYSICS G06 - COMPUTING G06T - IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
G06T11/60 - Editing figures and text
G06T2207/10016 - Video
G06T2207/10024 - Color image
G06T2207/10036 - Multispectral image
G06T2207/10044 - Radar image
G06T2207/10048 - Infrared image
G06T2207/20036 - Morphological image processing
G06T2207/20072 - Graph-based image processing
G06T2207/30232 - Surveillance
G06T7/11 - Region-based segmentation
G06T7/162 - involving graph-based methods

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DOE Contract Number:: AC04-94AL85000

Resource Type:: Patent

Resource Relation:: Patent File Date: 2015 Sep 08

Country of Publication:: United States

Language:: English

Subject:: 47 OTHER INSTRUMENTATION

Citation Formats


                    Brost, Randolph, McLendon, III, William C., Parekh, Ojas D., Rintoul, Mark Daniel, Watson, Jean-Paul, Strip, David R., and Diegert, Carl. Representation of activity in images using geospatial temporal graphs.  United States: N. p., 2018. 
        Web.

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                    Brost, Randolph, McLendon, III, William C., Parekh, Ojas D., Rintoul, Mark Daniel, Watson, Jean-Paul, Strip, David R., & Diegert, Carl. Representation of activity in images using geospatial temporal graphs.  United States.

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                    Brost, Randolph, McLendon, III, William C., Parekh, Ojas D., Rintoul, Mark Daniel, Watson, Jean-Paul, Strip, David R., and Diegert, Carl. Tue .  
        "Representation of activity in images using geospatial temporal graphs".  United States.  https://www.osti.gov/servlets/purl/1438449.

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@article{osti_1438449,

  title        = {Representation of activity in images using geospatial temporal graphs},

  author       = {Brost, Randolph and McLendon, III, William C. and Parekh, Ojas D. and Rintoul, Mark Daniel and Watson, Jean-Paul and Strip, David R. and Diegert, Carl},

  abstractNote = {Various technologies pertaining to modeling patterns of activity observed in remote sensing images using geospatial-temporal graphs are described herein. Graphs are constructed by representing objects in remote sensing images as nodes, and connecting nodes with undirected edges representing either distance or adjacency relationships between objects and directed edges representing changes in time. Activity patterns may be discerned from the graphs by coding nodes representing persistent objects like buildings differently from nodes representing ephemeral objects like vehicles, and examining the geospatial-temporal relationships of ephemeral nodes within the graph.},

  doi          = {},

  journal      = {},
number       = ,

  volume       = ,

  place        = {United States},

  year         = {2018},

  month        = {5}

}

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Works referenced in this record:

Aspect coherence for graph-based semantic image labelling
journal, January 2010

Passino, G.; Patras, I.; Izquierdo, E.
IET Computer Vision, Vol. 4, Issue 3, p. 183-194
https://doi.org/10.1049/iet-cvi.2008.0093

Learning to map between ontologies on the semantic web
conference, January 2002

Doan, AnHai; Madhavan, Jayant; Domingos, Pedro
WWW '02 Proceedings of the 11th international conference on World Wide Web, p. 662-673
https://doi.org/10.1145/511446.511532

Jackpine: A benchmark to evaluate spatial database performance
conference, April 2011

Ray, Suprio; Simion, Bogdan; Demke Brown, Angela
Data Engineering (ICDE)
https://doi.org/10.1109/ICDE.2011.5767929

Method and system for tracking and behavioral monitoring of multiple objects moving through multiple fields-of-view
patent-application, December 2005

Buehler, Christopher; Brock, Neil; Edulbehram, Jehanbux
US Patent Application 11/191128; 20050265582
URL: https://image-ppubs.uspto.gov/dirsearch-public/print/downloadPdf/20050265582

Geometric Hitting Set for Segments of Few Orientations
book, January 2015

Fekete, Sándor P.; Huang, Kan; Mitchell, Joseph S. B.
Approximation and Online Algorithms, p. 145-157
https://doi.org/10.1007/978-3-319-28684-6_13

Encoding and analyzing aerial imagery using geospatial semantic graphs
report, February 2014

Watson, Jean-Paul; Strip, David R.; McLendon, William C.
SAND2014-1405
https://doi.org/10.2172/1204099

Trajectory parsing by cluster sampling in spatio-temporal graph
conference, June 2009

Liu, Xiaobai; Lin, Liang; Zhu, Song-Chun
2009 IEEE Conference on Computer Vision and Pattern Recognition
https://doi.org/10.1109/CVPR.2009.5206688

A computational framework for ontologically storing and analyzing very large overhead image sets
conference, November 2014

Brost, Randy C.; McLendon, William C.; Parekh, Ojas
BigSpatial '14 Proceedings of the 3rd ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data, p. 1-10
https://doi.org/10.1145/2676536.2676537

Computing quality scores and uncertainty for approximate pattern matching in geospatial semantic graphs
journal, September 2015

Stracuzzi, David J.; Brost, Randy C.; Phillips, Cynthia A.
Statistical Analysis and Data Mining: The ASA Data Science Journal, Vol. 8, Issue 5-6, p. 340-352
https://doi.org/10.1002/sam.11294

Video-based vehicle detection and tracking using spatio-temporal maps
patent, January 2013

Malinovskiy, Yegor; Wang, Yinhai; Wu, Yao-Jan
US Patent Document 8,358,808
URL: https://image-ppubs.uspto.gov/dirsearch-public/print/downloadPdf/8358808

Methods and Systems for Content Processing
patent-application, February 2010

Conwell, William
US Patent Application 12/271692; 20100046842
URL: https://image-ppubs.uspto.gov/dirsearch-public/print/downloadPdf/20100046842

Geospatial-temporal semantic graph representations of trajectories from remote sensing and geolocation data
patent, August 2017

Perkins, David Nikolaus; Brost, Randolph C.; Ray, Lawrence P.
US Patent Document 9,727,976
URL: https://image-ppubs.uspto.gov/dirsearch-public/print/downloadPdf/9727976

Geospatial multiviewer
patent, July 2015

Hourie, Craig; Sulte, Steve
US Patent Document 9,076,259
URL: https://image-ppubs.uspto.gov/dirsearch-public/print/downloadPdf/9076259

Geospatial multiviewer
patent-application, March 2013

Hourie, Craig
US Patent Application 13/232559; 20130063489
URL: https://image-ppubs.uspto.gov/dirsearch-public/print/downloadPdf/20130063489

Classification and feature extraction for remote sensing images from urban areas based on morphological transformations
journal, September 2003

Benediktsson, J. A.; Pesaresi, M.; Arnason, K.
IEEE Transactions on Geoscience and Remote Sensing, Vol. 41, Issue 9, p. 1940-1949
https://doi.org/10.1109/TGRS.2003.814625

Method and system for performing image re-identification
patent, May 2010

Tu, Peter Henry; Sebastian, Thomas Baby; Rittscher, Jens
US Patent Document 7,711,146
URL: https://image-ppubs.uspto.gov/dirsearch-public/print/downloadPdf/7711146

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Similar Records

Title: Representation of activity in images using geospatial temporal graphs

Abstract

Citation Formats

Aspect coherence for graph-based semantic image labelling journal, January 2010

Learning to map between ontologies on the semantic web conference, January 2002

Jackpine: A benchmark to evaluate spatial database performance conference, April 2011

Method and system for tracking and behavioral monitoring of multiple objects moving through multiple fields-of-view patent-application, December 2005

Geometric Hitting Set for Segments of Few Orientations book, January 2015

Encoding and analyzing aerial imagery using geospatial semantic graphs report, February 2014

Trajectory parsing by cluster sampling in spatio-temporal graph conference, June 2009

A computational framework for ontologically storing and analyzing very large overhead image sets conference, November 2014

Computing quality scores and uncertainty for approximate pattern matching in geospatial semantic graphs journal, September 2015

Video-based vehicle detection and tracking using spatio-temporal maps patent, January 2013

Methods and Systems for Content Processing patent-application, February 2010

Geospatial-temporal semantic graph representations of trajectories from remote sensing and geolocation data patent, August 2017

Geospatial multiviewer patent, July 2015

Geospatial multiviewer patent-application, March 2013

Classification and feature extraction for remote sensing images from urban areas based on morphological transformations journal, September 2003

Method and system for performing image re-identification patent, May 2010

Aspect coherence for graph-based semantic image labelling
journal, January 2010

Learning to map between ontologies on the semantic web
conference, January 2002

Jackpine: A benchmark to evaluate spatial database performance
conference, April 2011

Method and system for tracking and behavioral monitoring of multiple objects moving through multiple fields-of-view
patent-application, December 2005

Geometric Hitting Set for Segments of Few Orientations
book, January 2015

Encoding and analyzing aerial imagery using geospatial semantic graphs
report, February 2014

Trajectory parsing by cluster sampling in spatio-temporal graph
conference, June 2009

A computational framework for ontologically storing and analyzing very large overhead image sets
conference, November 2014

Computing quality scores and uncertainty for approximate pattern matching in geospatial semantic graphs
journal, September 2015

Video-based vehicle detection and tracking using spatio-temporal maps
patent, January 2013

Methods and Systems for Content Processing
patent-application, February 2010

Geospatial-temporal semantic graph representations of trajectories from remote sensing and geolocation data
patent, August 2017

Geospatial multiviewer
patent, July 2015

Geospatial multiviewer
patent-application, March 2013

Classification and feature extraction for remote sensing images from urban areas based on morphological transformations
journal, September 2003

Method and system for performing image re-identification
patent, May 2010