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Title: Efficient track-before detect algorithm with minimal prior knowledge

Abstract

Apparatus, system and method for tracking an image target in a system, wherein a system receives an image comprising a plurality of pixels. The received image is processed via a plurality of different recursive motion model kernels in parallel to provide a plurality of kernel outputs, wherein each of the motion model kernels may include a respective pixel mask. Per-pixel energy is estimated of at least some of the plurality of kernel outputs. Velocity of at least one of the image pixels may also be estimated by generating a directional energy vector for each motion model kernel. The per-pixel energy and velocity estimates are fused to produce a fused estimate representing at least some of the motion model kernels for the image.

Inventors:
;
Issue Date:
Research Org.:
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1600166
Patent Number(s):
10445862
Application Number:
15/407,104
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
G - PHYSICS G06 - COMPUTING G06F - ELECTRIC DIGITAL DATA PROCESSING
DOE Contract Number:  
AC04-94AL85000
Resource Type:
Patent
Resource Relation:
Patent File Date: 01/16/2017
Country of Publication:
United States
Language:
English
Subject:
42 ENGINEERING

Citation Formats

Merry, Kyle, and Hansen, Ross L. Efficient track-before detect algorithm with minimal prior knowledge. United States: N. p., 2019. Web.
Merry, Kyle, & Hansen, Ross L. Efficient track-before detect algorithm with minimal prior knowledge. United States.
Merry, Kyle, and Hansen, Ross L. Tue . "Efficient track-before detect algorithm with minimal prior knowledge". United States. https://www.osti.gov/servlets/purl/1600166.
@article{osti_1600166,
title = {Efficient track-before detect algorithm with minimal prior knowledge},
author = {Merry, Kyle and Hansen, Ross L.},
abstractNote = {Apparatus, system and method for tracking an image target in a system, wherein a system receives an image comprising a plurality of pixels. The received image is processed via a plurality of different recursive motion model kernels in parallel to provide a plurality of kernel outputs, wherein each of the motion model kernels may include a respective pixel mask. Per-pixel energy is estimated of at least some of the plurality of kernel outputs. Velocity of at least one of the image pixels may also be estimated by generating a directional energy vector for each motion model kernel. The per-pixel energy and velocity estimates are fused to produce a fused estimate representing at least some of the motion model kernels for the image.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2019},
month = {10}
}

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