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 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,...
Muscles for Facial Expressions01:14

Muscles for Facial Expressions

The craniofacial muscles are a collection of approximately 20 thin skeletal muscles situated beneath the skin of the face and scalp. These muscles, primarily responsible for the vast array of human facial expressions, originate from the bones or fibrous structures of the skull and extend outwards to connect with the skin. While most skeletal muscles in the body are enveloped in thick fascia, facial muscles generally have a more delicate fascial covering, with the buccinator muscle being a...
Force Classification01:22

Force Classification

Forces play a crucial role in the study of physics and engineering. They are essential in describing the motion, behavior, and equilibrium of objects in the physical world. Forces can be classified based on their origin, type, and direction of action.
Contact and non-contact forces are two of the most widely used categories of forces. As the name suggests, contact forces require physical contact between two objects to act upon each other. Examples of contact forces include frictional,...
Residuals and Least-Squares Property01:11

Residuals and Least-Squares Property

The vertical distance between the actual value of y and the estimated value of y. In other words, it measures the vertical distance between the actual data point and the predicted point on the line
If the observed data point lies above the line, the residual is positive, and the line underestimates the actual data value for y. If the observed data point lies below the line, the residual is negative, and the line overestimates the actual data value for y.
The process of fitting the best-fit...
Prosopagnosia01:24

Prosopagnosia

Prosopagnosia, also known as face blindness, is the inability to recognize faces. In severe cases, individuals with prosopagnosia may not recognize close family members, including parents and spouses, by their faces. For instance, someone with prosopagnosia might walk past their child in a crowd, only realizing their mistake upon noticing their child's distinctive backpack or favorite jacket. Prosopagnosia specifically impairs facial recognition, while the recognition of other objects or...

You might also read

Related Articles

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

Sort by
Same author

Integrating polygenic risk scores in the prediction of type 2 diabetes risk and subtypes in British Pakistanis and Bangladeshis: A population-based cohort study.

PLoS medicine·2022
Same author

The early-life exposome modulates the effect of polymorphic inversions on DNA methylation.

Communications biology·2022
Same author

Early-life respiratory tract infections and the risk of school-age lower lung function and asthma: a meta-analysis of 150 000 European children.

The European respiratory journal·2022
Same author

The Emergence of Psychiatry: 1650-1850.

The American journal of psychiatry·2022
Same author

Identification of autosomal cis expression quantitative trait methylation (cis eQTMs) in children's blood.

eLife·2022
Same author

Short- and medium-term air pollution exposure, plasmatic protein levels and blood pressure in children.

Environmental research·2022
Same journal

HardFlow: Hard-Constrained Sampling for Flow-Matching Models Via Trajectory Optimization.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

Industrial Brain: Self-Evolving Neuro-Symbolic Autonomy with Causal Resilience for Cyber-Physical Systems.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

Adaptive Hardness-Driven Dictionary Distillation for Incomplete Streaming View Clustering.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

Mixture of Global and Local Experts with Diffusion Transformer for Controllable Face Generation.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

Task-KV: Task-aware KV Cache Optimization via Semantic Differentiation of Attention Heads.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

Achieving Text-based Person Retrieval with Any Granularity.

IEEE transactions on pattern analysis and machine intelligence·2026
See all related articles

Related Experiment Videos

Robust face recognition via sparse representation.

John Wright1, Allen Y Yang, Arvind Ganesh

  • 1Coordinated Science Laboratory, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA. jnwright@uiuc.edu

IEEE Transactions on Pattern Analysis and Machine Intelligence
|December 27, 2008
PubMed
Summary
This summary is machine-generated.

This study introduces a novel face recognition algorithm using sparse signal representation. The method enhances accuracy and robustness to occlusion by focusing on feature computation over feature type.

Related Experiment Videos

Area of Science:

  • Computer Vision
  • Machine Learning
  • Signal Processing

Background:

  • Automatic human face recognition is challenging due to variations in expression, illumination, occlusion, and disguise.
  • Existing methods often rely on specific feature extraction techniques, limiting their generalizability.

Purpose of the Study:

  • To develop a general image-based object recognition framework using sparse signal representation.
  • To address critical issues in face recognition, specifically feature extraction and robustness to occlusion.

Main Methods:

  • The problem is framed as classifying among multiple linear regression models.
  • A sparse representation is computed using L1-minimization.
  • A general classification algorithm for object recognition is proposed based on this sparse representation.

Main Results:

  • Feature choice becomes less critical when sparsity is leveraged; sufficient feature dimensions and correct sparse representation computation are key.
  • Unconventional features (e.g., downsampled images, random projections) perform comparably to conventional ones (e.g., Eigenfaces, Laplacianfaces) above a theoretical threshold.
  • The framework uniformly handles occlusion and corruption by exploiting their sparse nature in the pixel basis.

Conclusions:

  • Sparse representation theory provides a powerful framework for robust face recognition, offering insights into feature selection and occlusion handling.
  • The proposed algorithm demonstrates high efficacy in extensive experiments, validating its performance and theoretical predictions.
  • The method enhances robustness to occlusion and guides the selection of training data for improved performance.