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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...
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...
Relative Motion Analysis using Rotating Axes - Acceleration01:22

Relative Motion Analysis using Rotating Axes - Acceleration

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. The absolute velocity of point B is determined by adding the absolute velocity of point A, the relative velocity of point B in the rotating frame, and the effects caused by the angular velocity within the rotating frame.
Time differentiation is...
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...
Relative Motion Analysis - Acceleration01:10

Relative Motion Analysis - Acceleration

A slider-crank mechanism converts rotational motion from the crank into linear motion of the slider or vice versa. This mechanism consists of three main parts: the crank, the connecting rod, and the slider. The movement of the slider-crank is an example of general plane motion as the fluctuating angle between the crank and the connecting rod. Consider a segment AB where point A is at the end of the slider and point B is on the diametrically opposite end to point A, on a crack. The variance in...
Linear Approximation in Time Domain01:21

Linear Approximation in Time Domain

Nonlinear systems often require sophisticated approaches for accurate modeling and analysis, with state-space representation being particularly effective. This method is especially useful for systems where variables and parameters vary with time or operating conditions, such as in a simple pendulum or a translational mechanical system with nonlinear springs.
For a simple pendulum with a mass evenly distributed along its length and the center of mass located at half the pendulum's length, the...

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Related Experiment Video

Updated: Jun 1, 2026

Sample Drift Correction Following 4D Confocal Time-lapse Imaging
10:04

Sample Drift Correction Following 4D Confocal Time-lapse Imaging

Published on: April 12, 2014

Real-time affine global motion estimation using phase correlation and its application for digital image

Sanjeev Kumar1, Haleh Azartash, Mainak Biswas

  • 1Electrical and Computer Engineering Department, University of California at San Diego, La Jolla, CA 92093, USA.

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|May 25, 2011
PubMed
Summary
This summary is machine-generated.

This study introduces a fast and robust algorithm for estimating global motion in images using phase correlation and least squares. The method accurately stabilizes digital images, even with large motions and outliers.

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

Published on: December 3, 2013

Related Experiment Videos

Last Updated: Jun 1, 2026

Sample Drift Correction Following 4D Confocal Time-lapse Imaging
10:04

Sample Drift Correction Following 4D Confocal Time-lapse Imaging

Published on: April 12, 2014

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

Area of Science:

  • Computer Vision
  • Image Processing
  • Digital Signal Processing

Background:

  • Global motion estimation is crucial for video analysis and image stabilization.
  • Existing methods struggle with large motions, outliers, and computational complexity.

Purpose of the Study:

  • To develop a fast, robust, and accurate 2D-affine global motion estimation algorithm.
  • To apply the algorithm for effective digital image stabilization.

Main Methods:

  • Phase correlation in the Fourier-Mellin domain for initial motion estimation.
  • Pyramid-based approach for handling large motion ranges.
  • Robust least squares fitting with RANSAC for refining sparse motion vectors.
  • Block-based subpixel-accurate phase correlation on high-activity regions.

Main Results:

  • The algorithm achieves fast and robust 2D-affine motion estimation.
  • Rotation-scale-translation (RST) approximation ensures convergence for a wide range of motions.
  • The method demonstrates high robustness against outliers like foreground objects and flat regions.
  • Experimental results show superior motion range estimation compared to other phase correlation and optical flow methods.

Conclusions:

  • The proposed algorithm offers a significant advancement in global motion estimation and digital image stabilization.
  • Its robustness and accuracy make it suitable for challenging real-world scenarios.
  • The method provides a reliable solution for applications requiring precise motion tracking and stabilization.