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

Absolute Motion Analysis- General Plane Motion01:24

Absolute Motion Analysis- General Plane Motion

Visualize a drone, with its propellers spinning rapidly, hovering mid-air. The fascinating movements and operations of this drone can be comprehended by applying the principle of general plane motion.
As the drone's propellers rotate, an upward force is generated that counteracts the force of gravity, enabling the drone to lift off from the ground. This initial movement of the drone is along a straight path, representing a form of translational motion. In this phase, every point on the drone...
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...
Relative Motion Analysis using Rotating Axes01:25

Relative Motion Analysis using Rotating Axes

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 instrumental in...
Planar Rigid-Body Motion01:22

Planar Rigid-Body Motion

Understanding the movement of a rigid body in planar motion involves recognizing that every particle within this body is traversing a path that maintains a consistent distance from a specific plane. This concept is fundamental in the study of physics and mechanical engineering, and it allows us to comprehend better how objects move in space.
Planar motion is typically divided into three distinct categories. The first is rectilinear translation, demonstrated by a subway train that moves along...

You might also read

Related Articles

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

Sort by
Same author

Mutant huntingtin disrupts TET1 transcription and alters DNA methylation in a Huntington's disease knock-in pig model.

Cell reports·2026
Same author

Numerical Investigation of Short-Channel Effects and RF Performance in Top-Gate In<sub>2</sub>O<sub>3</sub> Thin-Film Transistors.

Micromachines·2026
Same author

A self-supervised GNN-Transformer framework for weak microseismic signal identification.

Scientific reports·2026
Same author

Radiation shielding calculations and design for a novel multi-room carbon therapy facility (SIMM).

Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine·2026
Same author

Observation of QED Effects, Breit Interaction, and Electron Correlation in Highly Charged Au Ions Produced by a High-Power Laser.

Physical review letters·2026
Same author

Data-Driven Control of Insect Flapping Flight via Deep Reinforcement Learning.

IEEE transactions on visualization and computer graphics·2026

Related Experiment Video

Updated: May 7, 2026

In Vivo Quantification of Hip Arthrokinematics during Dynamic Weight-bearing Activities using Dual Fluoroscopy
07:43

In Vivo Quantification of Hip Arthrokinematics during Dynamic Weight-bearing Activities using Dual Fluoroscopy

Published on: July 2, 2021

Marker optimization for facial motion acquisition and deformation.

Binh H Le1, Mingyang Zhu, Zhigang Deng

  • 1University of Houston, Houston.

IEEE Transactions on Visualization and Computer Graphics
|September 14, 2013
PubMed
Summary
This summary is machine-generated.

This study presents a novel method for optimizing facial motion capture marker layouts. The approach ensures accurate and efficient facial performance capture, enhancing marker-based skinning and analysis.

More Related Videos

Measuring 3D In-vivo Shoulder Kinematics using Biplanar Videoradiography
06:09

Measuring 3D In-vivo Shoulder Kinematics using Biplanar Videoradiography

Published on: March 12, 2021

Movement Retraining using Real-time Feedback of Performance
08:16

Movement Retraining using Real-time Feedback of Performance

Published on: January 17, 2013

Related Experiment Videos

Last Updated: May 7, 2026

In Vivo Quantification of Hip Arthrokinematics during Dynamic Weight-bearing Activities using Dual Fluoroscopy
07:43

In Vivo Quantification of Hip Arthrokinematics during Dynamic Weight-bearing Activities using Dual Fluoroscopy

Published on: July 2, 2021

Measuring 3D In-vivo Shoulder Kinematics using Biplanar Videoradiography
06:09

Measuring 3D In-vivo Shoulder Kinematics using Biplanar Videoradiography

Published on: March 12, 2021

Movement Retraining using Real-time Feedback of Performance
08:16

Movement Retraining using Real-time Feedback of Performance

Published on: January 17, 2013

Area of Science:

  • Computer Graphics
  • Computer Vision
  • Biomedical Engineering

Background:

  • Marker-based facial motion capture is crucial for various applications.
  • Determining optimal marker placement for facial motion capture remains a significant challenge.
  • Existing methods lack systematic exploration of marker layout optimization.

Purpose of the Study:

  • To develop and validate a computational approach for optimizing facial motion capture marker layouts.
  • To address the long-standing problem of inefficient and suboptimal marker placement.
  • To enhance the accuracy and robustness of facial performance capture.

Main Methods:

  • Optimization of characteristic control points using high-resolution facial mesh sequences.
  • Application of a thin-shell linear deformation model with optional hard constraints (e.g., symmetry, multiresolution).
  • Systematic exploration and validation of the proposed marker layout computation approach.

Main Results:

  • Demonstrated effectiveness, robustness, and accuracy of the optimized marker layouts.
  • Successful guidance for minimal yet effective facial motion capture marker placement.
  • Validation of the approach through experiments and comparisons.

Conclusions:

  • The proposed method provides an effective solution for optimizing facial motion capture marker layouts.
  • This research advances marker-based facial performance capture and mesh skinning.
  • The findings offer practical implications for improving facial motion analysis and applications.