Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Association Areas of the Cortex

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,...

Facial Feedback Hypothesis

Facial Feedback Hypothesis

Charles Darwin proposed that facial expressions are an evolutionary adaptation for communication. He argued that these expressions are not influenced by culture but are universal across species. For example, a snarling expression with exposed teeth signals a threat in many animals, including humans. Darwin also suggested that displaying an emotion can intensify the feeling. Smiling, for example, could enhance one's sense of happiness. This idea laid the foundation for understanding the role of...

You might also read

Related Articles

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

Sort by

Same author

Video Reenactment as Inductive Bias for Content-Motion Disentanglement.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2022

Same author

Anomaly Detection Based on Zero-Shot Outlier Synthesis and Hierarchical Feature Distillation.

IEEE transactions on neural networks and learning systems·2020

Same author

Local Directional Ternary Pattern for Facial Expression Recognition.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2017

Same author

Spatiotemporal Directional Number Transitional Graph for Dynamic Texture Recognition.

IEEE transactions on pattern analysis and machine intelligence·2015

Same author

Content-aware dark image enhancement through channel division.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2012

Same author

A noise-aware coding scheme for texture classification.

Sensors (Basel, Switzerland)·2011

Same journal

Style-Aware Contrastive Test-Time Adaptation: A Dual-Cache Model for Robust Vision-Language Alignment.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026

Same journal

Semantic Frame Interpolation.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026

Same journal

Physics-Guided Cross-Modal Decoupling with Test-Time Adaptation for Hyperspectral Image Restoration.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026

Same journal

Change-Prior-Guided Unsupervised Change Detection of Heterogeneous Remote Sensing Images.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026

Same journal

AgonicDreamer: Enhancing Multi-View Consistency in Text-to-3D Generation via Rectified Score Distillation.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026

Same journal

BiCM-Prompt: Bidirectional Cross-Modal Prompt Tuning for Class-Incremental Learning on Multisource Remote Sensing Images.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026

See all related articles

Search research articles

Related Experiment Video

Updated: May 15, 2026

Dynamic Digital Biomarkers of Motor and Cognitive Function in Parkinson's Disease

Dynamic Digital Biomarkers of Motor and Cognitive Function in Parkinson's Disease

Published on: July 24, 2019

Local directional number pattern for face analysis: face and expression recognition.

Adin Ramirez Rivera¹, Jorge Rojas Castillo, Oksam Chae

¹Department of Computer Engineering, Kyung Hee University, Yongin-si 446-701, Korea. adin@khu.ac.kr

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society

|December 28, 2012

Summary

This summary is machine-generated.

This study introduces the Local Directional Number Pattern (LDN), a new method for face analysis. LDN effectively recognizes faces and expressions, showing consistent performance across various challenging conditions.

More Related Videos

Holistic Facial Composite Creation and Subsequent Video Line-up Eyewitness Identification Paradigm

Holistic Facial Composite Creation and Subsequent Video Line-up Eyewitness Identification Paradigm

Published on: December 24, 2015

Automated Two-dimensional Spatiotemporal Analysis of Mobile Single-molecule FRET Probes

Automated Two-dimensional Spatiotemporal Analysis of Mobile Single-molecule FRET Probes

Published on: November 23, 2021

Related Experiment Videos

Last Updated: May 15, 2026

Dynamic Digital Biomarkers of Motor and Cognitive Function in Parkinson's Disease

Dynamic Digital Biomarkers of Motor and Cognitive Function in Parkinson's Disease

Published on: July 24, 2019

Holistic Facial Composite Creation and Subsequent Video Line-up Eyewitness Identification Paradigm

Holistic Facial Composite Creation and Subsequent Video Line-up Eyewitness Identification Paradigm

Published on: December 24, 2015

Automated Two-dimensional Spatiotemporal Analysis of Mobile Single-molecule FRET Probes

Automated Two-dimensional Spatiotemporal Analysis of Mobile Single-molecule FRET Probes

Published on: November 23, 2021

Area of Science:

Computer Vision
Biometrics
Machine Learning

Background:

Accurate face and expression recognition are crucial for many applications.
Existing local feature descriptors face challenges with variations in illumination, noise, and expressions.
There is a need for more discriminative and robust feature descriptors for face analysis.

Purpose of the Study:

To propose a novel local feature descriptor, Local Directional Number Pattern (LDN).
To evaluate the effectiveness of LDN for face and expression recognition tasks.
To demonstrate the robustness of LDN under various challenging conditions.

Main Methods:

LDN encodes directional texture information using a compass mask and prominent direction indices.
The descriptor captures structural patterns and intensity transitions for enhanced discrimination.
Face images are divided into regions, LDN features are extracted, and concatenated into a feature vector.

Main Results:

The proposed LDN descriptor demonstrated consistent performance across variations in illumination, noise, expression, and time lapse.
Experiments showed LDN's effectiveness as a face descriptor in different face analysis tasks.
LDN produces a more discriminative code compared to existing methods.

Conclusions:

LDN is a robust and effective local feature descriptor for face and expression recognition.
The method's ability to encode directional texture information contributes to its discriminative power.
LDN shows significant potential for real-world face analysis applications.