Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Nonlinear correlation for estimating the motion of multiple objects in image sequences.

J B Burl1, S S Karampuri

  • 1Department of Electrical Engineering, Michigan Technological University, 1400 Townsend Drive, Houghton, Michigan 49931-1295, USA. burl@mtu.edu

Applied Optics
|March 25, 2008
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Tilt Estimation in Moderate-to-Strong Scintillation.

Applied optics·2008
Same author

Lessons learned in managed care.

Pharmacy practice management quarterly·1998
Same author

Geriatric nurse practitioners in long-term care: demonstration of effectiveness in managed care.

Journal of the American Geriatrics Society·1998
Same author

Demonstration of the cost-effectiveness of a nurse practitioner/physician team in long-term care facilities.

HMO practice·1994
Same author

A reduced order extended Kalman filter for sequential images containing a moving object.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·1993
Same author

A geriatric nurse practitioner/physician team in a long-term care setting.

HMO practice·1991
Same journal

Multifunctional reconfigurable terahertz metasurface based on vanadium dioxide phase transition: achieving broadband absorption and efficient polarization conversion.

Applied optics·2026
Same journal

High-Q-factor electromagnetically induced transparency utilizing quasi-bound states in the continuum in an all-dielectric terahertz metasurface.

Applied optics·2026
Same journal

Automated stitching interferometry for high-precision metrology of X-ray mirrors.

Applied optics·2026
Same journal

Experimental demonstration of an approach to designing a metal-dielectric DBR resonant cavity structure.

Applied optics·2026
Same journal

High-precision wavefront reconstruction from a single-shot interferogram using a physics-driven hybrid feature calibration network.

Applied optics·2026
Same journal

Ultra-high-Q Fano resonance based on coupled topological corner states in Kagome photonic crystals.

Applied optics·2026
See all related articles

A novel nonlinear correlation algorithm estimates object motion from image pairs without prior object information. This method directly identifies the number, motion, and size of moving objects in sequences.

Area of Science:

  • Computer Vision
  • Image Processing
  • Motion Estimation

Background:

  • Estimating object motion in image sequences is crucial for various applications.
  • Traditional methods often require prior knowledge of object characteristics or complex preprocessing steps like feature extraction and segmentation.

Purpose of the Study:

  • To propose a new nonlinear correlation algorithm for motion estimation from image pairs.
  • To develop a method that does not require a priori information about the objects (number, size, shape).
  • To avoid the need for feature extraction or image segmentation.

Main Methods:

  • A nonlinear correlation algorithm is employed to directly analyze image pairs.
  • The algorithm processes images without requiring predefined object models or segmentation.

Related Experiment Videos

  • It directly computes motion parameters from the correlation of image data.

    • Main Results:

    • The algorithm successfully estimates the motion of objects from image pairs.
    • It directly provides information on the number, motion, and size of moving objects.
    • Additional processing allows for the determination of object centroids.

    Conclusions:

    • The proposed nonlinear correlation algorithm offers a robust and efficient approach to motion estimation.
    • Its ability to work without prior object information or segmentation simplifies the process.
    • The method demonstrates practical utility in analyzing image sequences.