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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...

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-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...

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.
When an external force is exerted, it sets the crank into a rotational movement. This, in turn, instigates the motion of the connecting rod, leading to what is referred to as a general plane motion. This process involves two key points - point A on the connecting rod...

Linear Approximation in Frequency Domain

Linear Approximation in Frequency Domain

Linear systems are characterized by two main properties: superposition and homogeneity. Superposition allows the response to multiple inputs to be the sum of the responses to each individual input. Homogeneity ensures that scaling an input by a scalar results in the response being scaled by the same scalar.
In contrast, nonlinear systems do not inherently possess these properties. However, for small deviations around an operating point, a nonlinear system can often be approximated as linear.

Relative Motion Analysis using Rotating Axes - Acceleration

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...

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Related Experiment Videos

Motion estimation using low-band-shift method for wavelet-based moving-picture coding.

H W Park¹, H S Kim

¹Dept. of Electr. Eng., Korea Adv. Inst. of Sci. and Technol., Taejon. hwpark@athena.kaist.ac.kr

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

|February 8, 2008

Summary

This study introduces a novel low-band-shift method to improve wavelet-domain motion estimation and compensation. The proposed discrete wavelet transform (DWT) approach overcomes shift-invariance, enhancing efficiency and image quality.

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Area of Science:

Image Processing
Signal Analysis
Computer Vision

Background:

Discrete Wavelet Transform (DWT) offers multiresolution analysis and subband decomposition for image processing.
The inherent shift-variant property of DWT due to decimation hinders efficient wavelet-domain motion estimation and compensation.

Purpose of the Study:

To address the shift-variant property in DWT for improved motion estimation.
To present a novel wavelet-domain motion estimation and compensation method.

Main Methods:

A low-band-shift method is proposed to overcome the shift-variant issue.
Motion estimation and compensation are performed within the wavelet domain using the proposed method.

Main Results:

The proposed method demonstrates superior performance compared to conventional techniques.
Improvements are observed in both Mean Absolute Difference (MAD) and subjective image quality.

Conclusions:

The developed wavelet-domain motion estimation method effectively overcomes shift-invariance.
This approach offers a robust and efficient solution for motion estimation, comparable to spatial domain methods.