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Absolute Motion Analysis- General Plane Motion

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

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...

Relative Motion Analysis using Rotating Axes-Problem Solving

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...

Curvilinear Motion: Rectangular Components

Curvilinear Motion: Rectangular Components

Curvilinear motion characterizes the movement of a particle or object along a curved path, notably evident when envisioning a car navigating a winding road. If the car starts at point A, its position vector is established within a fixed frame of reference, where the ratio of the position vector to its magnitude signifies the unit vector pointing in the position vector's direction.
As the car advances, its position evolves over time. Quantifying the car's velocity involves computing the time...

Non-uniform Circular Motion

Non-uniform Circular Motion

In uniform circular motion, the particle executing circular motion has a constant speed, and the circle is at a fixed radius. However, not all circular motion occurs at a constant speed. A particle can travel in a circle and speed up or slow down, showing an acceleration in the direction of motion. In that case, the motion is called non-uniform circular motion, and an additional acceleration is introduced, which is in the direction tangential to the circle.
For example, such accelerations...

Relative Motion Analysis - Velocity

Relative Motion Analysis - Velocity

A stroke engine has a slider-crank mechanism that 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.
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Related Experiment Video

Updated: Jul 7, 2026

Motion-Acuity Test for Visual Field Acuity Measurement with Motion-Defined Shapes

Motion-Acuity Test for Visual Field Acuity Measurement with Motion-Defined Shapes

Published on: February 23, 2024

Nonuniform image motion estimation using the maximum a posteriori principle.

N M Namazi¹, J I Lipp

¹Dept. of Electr. Eng., Catholic Univ. of America, Washington, DC.

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society

|January 1, 1992

Summary

This study introduces an iterative motion estimation algorithm for noisy images. The novel approach utilizes Gaussian assumptions for motion vector coefficients, improving accuracy in video analysis.

Related Experiment Videos

Last Updated: Jul 7, 2026

Motion-Acuity Test for Visual Field Acuity Measurement with Motion-Defined Shapes

Motion-Acuity Test for Visual Field Acuity Measurement with Motion-Defined Shapes

Published on: February 23, 2024

Area of Science:

Computer Vision
Image Processing
Signal Processing

Background:

Accurate frame-to-frame motion estimation is crucial for video compression and analysis.
Existing algorithms struggle with noisy image sequences, impacting performance.
The Karhunen-Loeve transform is a powerful tool for signal representation.

Purpose of the Study:

To develop a robust iterative motion estimation algorithm for noisy images.
To leverage statistical properties of motion vectors for improved accuracy.
To compare the proposed algorithm against established methods.

Main Methods:

An iterative scheme based on the generalized maximum likelihood (GML) algorithm.
Incorporation of the maximum a posteriori (MAP) criterion.
Assumption of zero-mean, Gaussian random variables for Karhunen-Loeve coefficients of motion vectors.

Main Results:

Development of a novel iterative motion estimator.
Linear analysis and discussion of algorithm convergence.
Simulation experiments demonstrating performance.

Conclusions:

The proposed iterative scheme offers a robust method for motion estimation in noisy images.
The algorithm shows competitive or improved performance compared to existing methods.
The statistical assumptions provide a strong foundation for motion estimation accuracy.