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

You might also read

Related Articles

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

Sort by
Same author

Automatic Data Reduction of Image Sequences Acquired in Object Tracking Mode for Detection and Position Measurement of Faint Orbital Objects.

Sensors (Basel, Switzerland)·2026
Same author

Fully Convolutional Neural Network for Vehicle Speed and Emergency-Brake Prediction.

Sensors (Basel, Switzerland)·2024
Same author

Part-Based Obstacle Detection Using a Multiple Output Neural Network.

Sensors (Basel, Switzerland)·2022
Same author

Robust Data Association Using Fusion of Data-Driven and Engineered Features for Real-Time Pedestrian Tracking in Thermal Images.

Sensors (Basel, Switzerland)·2021
Same author

A Self-Calibrating Probabilistic Framework for 3D Environment Perception Using Monocular Vision.

Sensors (Basel, Switzerland)·2020
Same author

Real-Time Detection and Measurement of Eye Features from Color Images.

Sensors (Basel, Switzerland)·2016

Related Experiment Video

Updated: Feb 16, 2026

High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques
11:34

High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques

Published on: December 3, 2013

16.1K

High-Speed Video System for Micro-Expression Detection and Recognition.

Diana Borza1, Radu Danescu2, Razvan Itu3

  • 1Computer Science Department, Technical University of Cluj-Napoca, 28 Memorandumului Street, 400114 Cluj Napoca, Romania. diana.borza@cs.ucluj.ro.

Sensors (Basel, Switzerland)
|December 15, 2017
PubMed
Summary

This study introduces an efficient system for analyzing micro-expressions, which are fleeting facial movements indicating concealed emotions. The proposed method accurately detects and classifies these subtle expressions, outperforming complex existing techniques.

Keywords:
affective computingdifference imagesfacial expression recognitionmicro-expression recognitionmicro-expression spotting

More Related Videos

Micro-particle Image Velocimetry for Velocity Profile Measurements of Micro Blood Flows
07:53

Micro-particle Image Velocimetry for Velocity Profile Measurements of Micro Blood Flows

Published on: April 25, 2013

17.8K
Video-rate Scanning Confocal Microscopy and Microendoscopy
14:10

Video-rate Scanning Confocal Microscopy and Microendoscopy

Published on: October 20, 2011

28.6K

Related Experiment Videos

Last Updated: Feb 16, 2026

High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques
11:34

High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques

Published on: December 3, 2013

16.1K
Micro-particle Image Velocimetry for Velocity Profile Measurements of Micro Blood Flows
07:53

Micro-particle Image Velocimetry for Velocity Profile Measurements of Micro Blood Flows

Published on: April 25, 2013

17.8K
Video-rate Scanning Confocal Microscopy and Microendoscopy
14:10

Video-rate Scanning Confocal Microscopy and Microendoscopy

Published on: October 20, 2011

28.6K

Area of Science:

  • Computer Vision
  • Human-Computer Interaction
  • Psychology

Background:

  • Micro-expressions are crucial for non-verbal communication and detecting deception.
  • Their involuntary nature and brief duration (1/15-1/25s) pose significant challenges for automated analysis.

Purpose of the Study:

  • To develop a comprehensive system for micro-expression analysis.
  • To accurately detect the occurrence and classify the type of micro-expressions.

Main Methods:

  • Implemented a high-speed image acquisition setup and a software framework.
  • Utilized simple motion descriptors based on absolute image differences for detection and classification.
  • Employed 2D Gaussian probabilities for the recognition module.

Main Results:

  • The system successfully detected frames containing micro-expressions and classified their types.
  • Experiments on public databases demonstrated superior performance compared to state-of-the-art methods.
  • The proposed approach is computationally less intensive.

Conclusions:

  • The developed micro-expression analysis system is effective and efficient.
  • This technology offers a promising tool for understanding non-verbal cues and aiding in deceit detection.
  • The system's simplicity and performance make it a valuable advancement in the field.