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Title: Trajectory analysis with geometric features

Abstract

Described herein are various technologies pertaining to extracting one or more features from trajectory data recorded during motion of a body, and further, generating a n-dimensional feature vector based upon the one or more extracted features. The n-dimensional feature vector enables expedited analysis of the trajectory data from which the feature vector was generated. For example, rather than having to analyze a trajectory curve comprising a large number of time-position data points, the n-dimensional feature vector can be compared with one or more search parameters to facilitate clustering of the trajectory data associated with the n-dimensional feature vector with other trajectory data which also satisfies the search request. The trajectory data can be plotted on a screen in combination with the n-dimensional feature vector, and other pertinent information. The trajectory data, etc., can be displayed using heat maps or other graphical representation.

Inventors:
;
Issue Date:
Research Org.:
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1568574
Patent Number(s):
10,345,106
Application Number:
14/927,083
Assignee:
National Technology & Engineering Solutions of Sandia, LLC (Albuquerque, NM)
DOE Contract Number:  
AC04-94AL85000
Resource Type:
Patent
Resource Relation:
Patent File Date: 10/29/2015
Country of Publication:
United States
Language:
English

Citation Formats

Wilson, Andrew T., and Rintoul, Mark Daniel. Trajectory analysis with geometric features. United States: N. p., 2019. Web.
Wilson, Andrew T., & Rintoul, Mark Daniel. Trajectory analysis with geometric features. United States.
Wilson, Andrew T., and Rintoul, Mark Daniel. Tue . "Trajectory analysis with geometric features". United States. https://www.osti.gov/servlets/purl/1568574.
@article{osti_1568574,
title = {Trajectory analysis with geometric features},
author = {Wilson, Andrew T. and Rintoul, Mark Daniel},
abstractNote = {Described herein are various technologies pertaining to extracting one or more features from trajectory data recorded during motion of a body, and further, generating a n-dimensional feature vector based upon the one or more extracted features. The n-dimensional feature vector enables expedited analysis of the trajectory data from which the feature vector was generated. For example, rather than having to analyze a trajectory curve comprising a large number of time-position data points, the n-dimensional feature vector can be compared with one or more search parameters to facilitate clustering of the trajectory data associated with the n-dimensional feature vector with other trajectory data which also satisfies the search request. The trajectory data can be plotted on a screen in combination with the n-dimensional feature vector, and other pertinent information. The trajectory data, etc., can be displayed using heat maps or other graphical representation.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2019},
month = {7}
}

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