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

Large-scale pose-invariant face recognition using cellular simultaneous recurrent network.

Yong Ren1, Khan M Iftekharuddin, William E White

  • 1Intelligent Systems and Image Processing Lab, Department of Electrical and Computer Engineering, University of Memphis, Memphis, Tennessee 38152, USA.

Applied Optics
|April 2, 2010
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

Association Areas of the Cortex01:21

Association Areas of the Cortex

Association areas are regions of the cerebral cortex that do not have a specific sensory or motor function. Instead, they integrate and interpret information from various sources to enable higher cognitive processes such as memory, learning, and decision-making. Some key association areas include the following:
Prefrontal Association Area: This area is located in the frontal lobe and is involved in planning, decision-making, and moderating social behavior. It connects with primary motor areas,...

You might also read

Related Articles

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

Sort by
Same author

Microstructure and Mechanical Properties of a Ti-Al-Mo-V-Cr-Sn-Zr Titanium Alloy via Double-Annealing Heat Treatment.

Materials (Basel, Switzerland)·2026
Same author

Deep-learning-based artificial intelligence approaches for grading and progression prediction of clear cell renal cell carcinoma.

iScience·2026
Same author

An interpretable multimodal fusion model for improving diagnosis and prognosis prediction of kidney allograft rejection.

Kidney research and clinical practice·2026
Same author

Predicting major organ complications in primary Sjögren's disease using a machine learning ensemble strategy: a dual-center retrospective clinical study.

Frontiers in immunology·2026
Same author

Neuroma Prevention with a Novel In Situ Forming Hydrogel in a Rat Sciatic Nerve Model.

Plastic and reconstructive surgery. Global open·2026
Same author

Lentiviral SgRNA Delivery for CRISPR/Cas9 Editing in Cre-Dependent Cas9 Knock-in Primary Mouse Hepatocytes.

Journal of visualized experiments : JoVE·2026
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

This study introduces a novel cellular simultaneous recurrent network (CSRN) for robust face recognition, achieving 77% accuracy with +/-90 degrees pose variations in image sequences.

Area of Science:

  • Computer Science
  • Artificial Intelligence
  • Biometrics

Background:

  • Face recognition systems struggle with significant pose variations.
  • Existing methods often require controlled environments or limited pose angles.

Purpose of the Study:

  • To develop a novel face recognition technique capable of handling large pose variations (+/-90 degrees) in image sequences.
  • To formulate face recognition with large pose variations as an implicit temporal prediction task.

Main Methods:

  • Utilized a cellular simultaneous recurrent network (CSRN) for implicit temporal prediction.
  • Employed a scale-space and facial structure-based algorithm for face extraction preprocessing.
  • Reduced computational cost by using eigenfaces of image sequences as input to CSRN.

Related Experiment Videos

  • Implemented a modified distance metric for comparing successive frames.

    • Main Results:

    • Achieved an overall face recognition rate of 77% on the VidTIMIT Audio-Video face dataset.
    • Demonstrated the effectiveness of CSRN in handling significant pose variations.

    Conclusions:

    • The proposed CSRN-based face recognition technique is effective for large pose variations.
    • The implicit temporal prediction approach within CSRN enables robust recognition in challenging conditions.