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}
}