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

Frames: Problem Solving II01:26

Frames: Problem Solving II

536
Consider a hydraulic hoist supporting a load of 1 kN. Assuming a simplified schematic representation of this frame structure, the force acting on BD and BF members can be determined.
536
Relative Motion Analysis using Rotating Axes01:25

Relative Motion Analysis using Rotating Axes

1.0K
Consider a component AB undergoing a linear motion. Along with a linear motion, point B also rotates around point A. To comprehend this complex movement, position vectors for both points A and B are established using a stationary reference frame.
However, to express the relative position of point B relative to point A, an additional frame of reference, denoted as x'y', is necessary. This additional frame not only translates but also rotates relative to the fixed frame, making it...
1.0K
Relative Motion Analysis using Rotating Axes-Problem Solving01:29

Relative Motion Analysis using Rotating Axes-Problem Solving

817
Consider a crane whose telescopic boom rotates with an angular velocity of 0.04 rad/s and angular acceleration of 0.02 rad/s2. Along with the rotation, the boom also extends linearly with a uniform speed of 5 m/s. The extension of the boom is measured at point D, which is measured with respect to the fixed point C on the other end of the boom. For the given instant, the distance between points C and D is 60 meters.
Here, in order to determine the magnitude of velocity and acceleration for point...
817

You might also read

Related Articles

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

Sort by
Same author

Toward Multimodal Privacy in XR: Design and Evaluation of Composite Privatization Methods for Gaze and Body Tracking Data.

IEEE transactions on visualization and computer graphics·2026
Same author

Privacy-Preserving Gaze Data Streaming in Immersive Interactive Virtual Reality: Robustness and User Experience.

IEEE transactions on visualization and computer graphics·2024
Same author

Privacy-preserving datasets of eye-tracking samples with applications in XR.

IEEE transactions on visualization and computer graphics·2023
Same author

Next-generation deep learning based on simulators and synthetic data.

Trends in cognitive sciences·2021
Same author

Sensor-Based Evaluation of Physical Therapy Exercises<sup></sup>.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2021
Same author

Fast Foveating Cameras for Dense Adaptive Resolution.

IEEE transactions on pattern analysis and machine intelligence·2021
Same journal

Graph Pattern Matching based reassembly - 3DGPM.

IEEE computer graphics and applications·2026
Same journal

Making Learning Visible: Turning Public Engagement into Evidence for Academic Learning.

IEEE computer graphics and applications·2026
Same journal

LlymX: Multimodal LLM-Augmented XR for Context-Aware Information Access.

IEEE computer graphics and applications·2026
Same journal

Dynamic Gaussian-Based Digital Twin Reconstruction of Articulated Multi-Joint Objects.

IEEE computer graphics and applications·2026
Same journal

Steiner and Poisson Traversal Initializations: Initial Curve Optimization for Geometric Flow-based Surface Filling.

IEEE computer graphics and applications·2026
Same journal

Insight Into the Insight Toolkit.

IEEE computer graphics and applications·2026
See all related articles

Related Experiment Video

Updated: Mar 16, 2026

Combining Eye-tracking Data with an Analysis of Video Content from Free-viewing a Video of a Walk in an Urban Park Environment
08:25

Combining Eye-tracking Data with an Analysis of Video Content from Free-viewing a Video of a Walk in an Urban Park Environment

Published on: May 7, 2019

9.7K

Predicting Moves-on-Stills for Comic Art Using Viewer Gaze Data.

Eakta Jain, Yaser Sheikh, Jessica Hodgins

    IEEE Computer Graphics and Applications
    |August 12, 2016
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces an algorithm that uses viewer gaze to automatically generate camera moves for comic art. This technique enhances digital comic experiences by mimicking professional DVD-style animations.

    More Related Videos

    Loneliness Assuaged: Eye-Tracking an Audience Watching Barrage Videos
    06:45

    Loneliness Assuaged: Eye-Tracking an Audience Watching Barrage Videos

    Published on: May 29, 2020

    4.7K
    A Methodology for Capturing Joint Visual Attention Using Mobile Eye-Trackers
    12:39

    A Methodology for Capturing Joint Visual Attention Using Mobile Eye-Trackers

    Published on: January 18, 2020

    8.3K

    Related Experiment Videos

    Last Updated: Mar 16, 2026

    Combining Eye-tracking Data with an Analysis of Video Content from Free-viewing a Video of a Walk in an Urban Park Environment
    08:25

    Combining Eye-tracking Data with an Analysis of Video Content from Free-viewing a Video of a Walk in an Urban Park Environment

    Published on: May 7, 2019

    9.7K
    Loneliness Assuaged: Eye-Tracking an Audience Watching Barrage Videos
    06:45

    Loneliness Assuaged: Eye-Tracking an Audience Watching Barrage Videos

    Published on: May 29, 2020

    4.7K
    A Methodology for Capturing Joint Visual Attention Using Mobile Eye-Trackers
    12:39

    A Methodology for Capturing Joint Visual Attention Using Mobile Eye-Trackers

    Published on: January 18, 2020

    8.3K

    Area of Science:

    • Computer Vision
    • Digital Media Arts
    • Human-Computer Interaction

    Background:

    • Comic art relies on sequential panels to convey narratives.
    • The move-on-stills technique digitally animates static comic panels using camera movements.
    • Current methods for creating move-on-stills require manual user input for camera parameters.

    Purpose of the Study:

    • To develop an algorithm that automatically predicts camera move parameters for comic art.
    • To leverage viewer gaze data as input for generating dynamic digital comic experiences.
    • To automate the creation of move-on-stills animations.

    Main Methods:

    • An algorithm was proposed that utilizes viewer gaze data.
    • The algorithm computationally predicts camera move parameters for comic panels.
    • The system was tested on diverse comic book panels.

    Main Results:

    • The algorithm successfully generated camera move parameters for comic art.
    • Performance evaluation involved comparing the algorithm's output with professional DVD productions.
    • Demonstrated the feasibility of gaze-driven animation for digital comics.

    Conclusions:

    • Viewer gaze is a viable input for automating camera move generation in digital comics.
    • The proposed algorithm offers a novel approach to creating dynamic comic art.
    • This research contributes to enhancing digital storytelling through automated animation techniques.