Image Processing for Multiple-Target Tracking on a Graphics Processing Unit

Abstract

Multiple-target tracking (MTT) systems have been implemented on many di?erent platforms, however these solutions are often expensive and have long development times. Such MTT implementations require custom hardware yet o?er very little flexibility with ever changing data sets and target tracking requirements. This research explores how to supplement and enhance MTT performance with an existing graphics processing unit (GPU) on a general computing platform. Typical computers are already equipped with powerful GPUs to support various games and multimedia applications. However, such GPUs are not currently being used in desktop MTT applications. Bottleneck MTT image processing functions (frame di?erencing) were converted to execute on the GPU. On average, the GPU code executed 287% faster than the MATLAB implementation. Some individual functions actually executed 20 times faster than the baseline. These results indicate that the GPU is a viable source to signi?cantly increase the performance of MTT with a low-cost hardware solution.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2009
Accession Number
ADA499529

Entities

People

  • Michael A. Tanner

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Biomedical
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Air Force
  • Algorithms
  • Central Processing Units
  • Computational Complexity
  • Computer Programming
  • Computer Programs
  • Computers
  • Data Association
  • Department Of Defense
  • Detectors
  • Graphics Processing Unit
  • Image Processing
  • Kalman Filters
  • Multiple Hypothesis Tracking
  • Multitarget Tracking
  • Operating Systems
  • Target Tracking

Fields of Study

  • Computer science

Readers

  • Electrical Engineering
  • Parallel and Distributed Computing.