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

Kinematic Equations for Rotation01:30

Kinematic Equations for Rotation

In mechanics, when one observes a rigid body in rotational motion with constant angular acceleration, it is possible to establish equations for its rotational kinematics. This process resembles how linear kinematics are dealt with in simpler motion studies.
For instance, imagine a point A on a rigid body engaged in circular motion. The translational velocity of this particular point can be calculated by taking the time derivatives of the displacement equation, which essentially measures the...
Kinematic Equations: Problem Solving01:15

Kinematic Equations: Problem Solving

When analyzing one-dimensional motion with constant acceleration, the problem-solving strategy involves identifying the known quantities and choosing the appropriate kinematic equations to solve for the unknowns. Either one or two kinematic equations are needed to solve for the unknowns, depending on the known and unknown quantities. Generally, the number of equations required is the same as the number of unknown quantities in the given example. Two-body pursuit problems always require two...
Kinematic Equations - III01:18

Kinematic Equations - III

The first two kinematic equations have time as a variable, but the third kinematic equation is independent of time. This equation expresses final velocity as a function of the acceleration and distance over which it acts. The fourth kinematic equation does not have an acceleration term and provides the final position of the object at time t in terms of the initial and final velocities. This equation is useful when the value of the constant acceleration is unknown.
Using the kinematic equations,...
Kinematic Equations - II01:17

Kinematic Equations - II

The second kinematic equation expresses the final position of an object in terms of its initial position, the distance traveled with the initial constant velocity, and the distance traveled due to a change in velocity. Similar to the first kinematic equation, this equation is also only valid when the acceleration is constant throughout the motion of an object.
Suppose a car merges into freeway traffic on a 200 m long ramp. If its initial velocity is 10 m/s and it accelerates at 2 m/s2, then the...
Relative Motion Analysis using Rotating Axes-Problem Solving01:29

Relative Motion Analysis using Rotating Axes-Problem Solving

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...
Kinematic Equations - I01:26

Kinematic Equations - I

When an object moves with constant acceleration, the velocity of the object changes at a constant rate throughout the motion. The kinematic equations of motions are derived for such cases where the acceleration of the object is constant. The first kinematic equation gives an insight into the relationship between velocity, acceleration, and time. We can see, for example:

You might also read

Related Articles

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

Sort by
Same author

Advances in Electrocatalytic CO<sub>2</sub> Reduction Under Acidic Media: Interfacial Microenvironment, Catalyst Design, and Electrolyzers.

Small (Weinheim an der Bergstrasse, Germany)·2026
Same author

High-performance electrochemical sensing of 2-aminophenol enabled by a boron-doped diamond electrode.

RSC advances·2026
Same author

From Single Atom to Five-Atom Cluster Catalysts on Boron-Doped Diamond: Interface Engineering and Dynamic Active Sites Exploration for Acidic OER.

The journal of physical chemistry letters·2026
Same author

Research progress of high-entropy catalysts in electrochemical oxidation of organic small molecules.

Chemical communications (Cambridge, England)·2026
Same author

d-Orbital modulation of high-entropy sulfides with amorphous/crystalline heterostructures for simultaneous hydrogen production and sulfur recovery.

Chemical science·2026
Same author

Electronic Structure Modulation in High-Entropy@Cu<sub><i>x</i></sub>S<sub><i>y</i></sub> Heterostructured Nanorods via Interface Engineering for Enhanced Multifunctional Electrocatalysis.

Inorganic chemistry·2026

Related Experiment Video

Updated: Jun 13, 2026

Robotized Testing of Camera Positions to Determine Ideal Configuration for Stereo 3D Visualization of Open-Heart Surgery
05:12

Robotized Testing of Camera Positions to Determine Ideal Configuration for Stereo 3D Visualization of Open-Heart Surgery

Published on: August 12, 2021

Motion estimation for nonoverlapping multicamera rigs: linear algebraic and L{infinity} geometric solutions.

Jae-Hak Kim1, Hongdong Li, Richard Hartley

  • 1Department of Computer Science, Queen Mary, University of London, Mile End Road, London E14NS, United Kingdom. jaehak@dcs.qmul.ac.uk

IEEE Transactions on Pattern Analysis and Machine Intelligence
|May 1, 2010
PubMed
Summary

We developed two new algorithms for estimating multicamera rig motion, offering a fast linear solution and a guaranteed optimal geometric solution. These methods improve ego-motion estimation for systems with limited camera overlap.

Related Experiment Videos

Last Updated: Jun 13, 2026

Robotized Testing of Camera Positions to Determine Ideal Configuration for Stereo 3D Visualization of Open-Heart Surgery
05:12

Robotized Testing of Camera Positions to Determine Ideal Configuration for Stereo 3D Visualization of Open-Heart Surgery

Published on: August 12, 2021

Area of Science:

  • Computer Vision
  • Robotics
  • Geometric Estimation

Background:

  • Estimating ego-motion is crucial for autonomous systems.
  • Existing multicamera motion estimation methods often lack linear or guaranteed optimal solutions.
  • General Camera Model (GCM) is essential for flexible camera system representation.

Purpose of the Study:

  • To introduce two novel algorithms for estimating the 6 degrees of freedom ego-motion of a multicamera rig.
  • To address the challenge of motion estimation in multicamera systems with non-overlapping fields of view.
  • To provide both a fast linear and a globally optimal geometric solution.

Main Methods:

  • Developed a fast linear algebraic method based on the General Camera Model (GCM).
  • Proposed a globally optimal geometric algorithm using L{infinity} error minimization and branch-and-bound techniques.
  • Analyzed camera configuration degeneracy for the linear method and applied rotation space search for the geometric method.

Main Results:

  • The linear method provides a fast and efficient solution for ego-motion estimation.
  • The geometric L{infinity} algorithm guarantees globally optimal results.
  • Experiments on synthetic and real data demonstrate the effectiveness of both algorithms.

Conclusions:

  • The proposed linear and optimal geometric algorithms advance multicamera ego-motion estimation.
  • These methods are particularly effective for systems with challenging camera configurations.
  • The study offers significant contributions to the field of computer vision and robotics.