Real-Time Periodic Motion Detection, Analysis and Application

Abstract

We describe a new technique to detect and analyze periodic motion as seen from both a static and moving camera. By tracking objects of interest, we compute an object's self-similarity as it evolves in time. For periodic motion, the self-similarity measure is also periodic, and we apply time-frequency analysis to detect and characterize the periodic motion. A real-time system has been implemented to track and classify objects using periodicity. Examples of object classification, person counting, and non-stationary periodicity are provided.

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Document Details

Document Type
Technical Report
Publication Date
Jul 25, 1999
Accession Number
ADA387019

Entities

People

  • Larry Davis
  • Ross Cutler

Organizations

  • University of Maryland

Tags

Communities of Interest

  • Air Platforms

DTIC Thesaurus Topics

  • Algorithms
  • Boundaries
  • Cameras
  • Classification
  • Computer Science
  • Computer Vision
  • Detection
  • Fourier Analysis
  • Frequency
  • Low Resolution
  • Periodic Variations
  • Power Spectra
  • Spectra
  • Stationary
  • Surveillance
  • Universities
  • Video Surveillance

Readers

  • Computational Modeling and Simulation
  • Image Processing and Computer Vision.
  • Statistical inference.