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 Video

Updated: May 22, 2026

End-To-End Deep Neural Network for Salient Object Detection in Complex Environments
03:31

End-To-End Deep Neural Network for Salient Object Detection in Complex Environments

Published on: December 15, 2023

Appearance-based gaze estimation using visual saliency.

Yusuke Sugano1, Yasuyuki Matsushita, Yoichi Sato

  • 1Sato Laboratory, Institute of Industrial Science, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505, Japan. sugano@iis.u-tokyo.ac.jp

IEEE Transactions on Pattern Analysis and Machine Intelligence
|May 2, 2012
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

Overlapping premorbid frailty, multimorbidity and malnutrition and their associations with poor outcomes in patients with stroke.

Age and ageing·2026
Same author

Multiagent First-Person Perspective Analysis for Leadership Assessment in Pediatric Emergency Simulations: A Feasibility Study.

Critical care explorations·2026
Same author

DP-SfM: Dual-Pixel Structure-from-Motion without Scale Ambiguity.

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

Tiny integrated lasers and their application to industrial laser technologies: feature issue introduction.

Optics express·2026
Same author

Induction of Human β-Defensin-2 by Vaginal <i>Lactobacillus crispatus</i> Strains in Vaginal Epithelial Cells Correlates With Their Adhesion Abilities.

Open forum infectious diseases·2026
Same author

Association of intradialytic hypotension and physical performance with fall and fracture incidence in hemodialysis patients: The REPnet-HD study.

Bone·2026
Same journal

TraGraph-GS: Trajectory Graph-based Gaussian Splatting for Arbitrary Large-Scale Scene Rendering.

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

SWIFT: A Small-World Interaction Framework for Flow-Aware Trajectory Prediction in Autonomous Driving.

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

This study introduces a novel gaze sensing method using visual saliency maps and eye images, eliminating the need for personal calibration. The technique achieves accurate gaze estimation for user attention analysis.

Area of Science:

  • Computer Vision
  • Human-Computer Interaction
  • Machine Learning

Background:

  • Gaze estimation is crucial for understanding user attention and interaction.
  • Existing methods often require explicit personal calibration, limiting their practicality.
  • Developing calibration-free gaze sensing remains a significant challenge.

Purpose of the Study:

  • To propose a novel gaze sensing method that does not require explicit personal calibration.
  • To create an effective gaze estimator using only eye images captured while a person watches a video.
  • To improve the accuracy and efficiency of gaze estimation for user attention analysis.

Main Methods:

  • Utilizing visual saliency maps of video frames as probability distributions for gaze points.

More Related Videos

A Gaze-Contingent Display Framework for Perceptual Learning Research with Simulated Central Vision Loss
07:12

A Gaze-Contingent Display Framework for Perceptual Learning Research with Simulated Central Vision Loss

Published on: April 11, 2025

Investigating the Deployment of Visual Attention Before Accurate and Averaging Saccades via Eye Tracking and Assessment of Visual Sensitivity
06:46

Investigating the Deployment of Visual Attention Before Accurate and Averaging Saccades via Eye Tracking and Assessment of Visual Sensitivity

Published on: March 18, 2019

Related Experiment Videos

Last Updated: May 22, 2026

End-To-End Deep Neural Network for Salient Object Detection in Complex Environments
03:31

End-To-End Deep Neural Network for Salient Object Detection in Complex Environments

Published on: December 15, 2023

A Gaze-Contingent Display Framework for Perceptual Learning Research with Simulated Central Vision Loss
07:12

A Gaze-Contingent Display Framework for Perceptual Learning Research with Simulated Central Vision Loss

Published on: April 11, 2025

Investigating the Deployment of Visual Attention Before Accurate and Averaging Saccades via Eye Tracking and Assessment of Visual Sensitivity
06:46

Investigating the Deployment of Visual Attention Before Accurate and Averaging Saccades via Eye Tracking and Assessment of Visual Sensitivity

Published on: March 18, 2019

  • Aggregating saliency maps based on eye image similarity to identify gaze points.
  • Employing Gaussian process regression to map eye images to gaze points.
  • Implementing a feedback loop to refine gaze probability maps and enhance estimation accuracy.

    • Main Results:

    • The proposed method demonstrates robust performance across different individuals and video content.
    • Achieved an accuracy of 3.5 degrees, suitable for estimating user attention on displays.
    • Successfully eliminated the need for explicit personal calibration in gaze sensing.

    Conclusions:

    • The developed gaze sensing method offers a practical and accurate solution for attention estimation.
    • The approach shows significant potential for applications in human-computer interaction and user behavior analysis.
    • Calibration-free gaze estimation using visual saliency and eye-tracking is feasible and effective.