Implementation of Efficient Pan-Tilt-Zoom Camera Calibration

Abstract

Pan-tilt-zoom (PTZ) cameras, frequently used in both online and automated surveillance applications, require accurate knowledge of camera parameters in order to accurately register autonomously tracked objects to a world model. Due to imprecision in the PTZ mechanism, these parameters cannot be obtained from PTZ control commands but must be calculated directly from camera imagery. This report describes the efforts to implement a real-time calibration system for a stationary PTZ camera. The approach continuously tracks distinctive image feature points from frame to frame, and from these correspondences, robustly calculates the homography transformation between frames. Camera internal parameters are then calculated from these homographies. Finally, the external parameters can be calculated from the internal parameters and image homographies. The calculations are performed by a self-contained program that continually monitors images collected by the camera as it performs pan, tilt, and zoom operations. The accuracy of the calculated calibration parameters are compared to ground truth data. The program works with a higher degree of accuracy for small changes in the camera's external parameters. In addition, long algorithm execution time prevents the algorithm from running under all real-time conditions.

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Document Details

Document Type
Technical Report
Publication Date
Apr 01, 2009
Accession Number
ADA497476

Entities

People

  • Nicholas Fung
  • Philip David

Organizations

  • United States Army Research Laboratory

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Accuracy
  • Algorithms
  • Aspect Ratio
  • Calibration
  • Cameras
  • Central Europe
  • Computer Graphics
  • Computer Vision
  • Distortion
  • Errors
  • Geometry
  • Information Science
  • Measurement
  • Military Research
  • Orientation (Direction)
  • Target Tracking
  • Zoom Lenses

Fields of Study

  • Physics

Readers

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