Object Tracking Through Adaptive Correlation

Abstract

This paper discusses the use of a correlation based system to track, an object through a series of images based on templates derived from previous image frames. The ability to track is extended to sequences which include multiple objects of interest within the field of view. This is accomplishes by comparing the height and shape of the template autocorrelation to the peaks in the correlation of the template with the next scene. The result is to identify the region in the next scene which best matches the designated target. In addition to correlation plane postprocessing, an adaptive window is used to determine the template size in order to reduce the effects of correlator walk- off. The image sequences used were taken from a Forward Looking Infrared (FLIR) sensor mounted onboard a DC-3 aircraft. The images contain a T-55 tank and both an M-113 and a TAB-71 armored personnel carrier moving in a columnized formation along a dirt road. The goals of this research were to (1) track targets in the presence of other, and sometimes brighter, targets of similar shape; (2) to maintain small tracking errors; and (3) to reduce the effects of correlator walk-off.... Correlation, Adaptive template, Tracking.

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Document Details

Document Type
Technical Report
Publication Date
Dec 17, 1992
Accession Number
ADA259448

Entities

People

  • Dennis A. Montera

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Air Platforms
  • C4I
  • Materials and Manufacturing Processes
  • Sensors
  • Weapons Technologies

DTIC Thesaurus Topics

  • Aircrafts
  • Algorithms
  • Artificial Intelligence
  • Autocorrelation
  • C Programming Language
  • Computer Programming
  • Computer Programs
  • Computers
  • Correlators
  • Electrical Engineering
  • Gray Scale
  • Image Processing
  • Images
  • Pattern Recognition
  • Signal Processing
  • Statistics
  • Students

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Computer Vision.