Jove
Visualize
Contact Us

Related Concept Videos

Residuals and Least-Squares Property01:11

Residuals and Least-Squares Property

The vertical distance between the actual value of y and the estimated value of y. In other words, it measures the vertical distance between the actual data point and the predicted point on the line
If the observed data point lies above the line, the residual is positive, and the line underestimates the actual data value for y. If the observed data point lies below the line, the residual is negative, and the line overestimates the actual data value for y.
The process of fitting the best-fit...
Curvilinear Motion: Rectangular Components01:23

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...
Gradient Vectors and Their Applications01:19

Gradient Vectors and Their Applications

Every point on a topographical map corresponds to a particular elevation, so the landscape can be modeled as a surface whose height depends on horizontal position. From any given location, a hiker may face infinitely many directions, but only one direction produces the fastest possible increase in elevation. This unique route is called the direction of steepest ascent, and in multivariable calculus, it is represented by the gradient vector of the elevation function.The gradient vector points...
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...
Relative Motion Analysis - Velocity01:24

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...
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...

You might also read

Related Articles

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

Sort by
Same author

Accuracy of a novel minimally invasive registration method for dynamic navigation-assisted zygomatic implant surgery: a pilot prospective single-arm study.

International journal of oral and maxillofacial surgery·2026
Same author

[Certain key questions in the diagnosis and treatment of primary osteoporosis and other disorders related to abnormal calcium and phosphorus metabolism].

Zhonghua yi xue za zhi·2025
Same author

Novel use of dynamic navigation for guiding a piezoelectric device during window osteotomy for maxillary sinus floor elevation in complex clinical scenarios.

International journal of oral and maxillofacial surgery·2024
Same author

[Biocompatibility of extracellular matrix hydrogel with human iPSCs differentiated cardiomyocytes].

Zhonghua xin xue guan bing za zhi·2021
Same author

Sequential hypoallergenic boiled peanut and roasted peanut oral immunotherapy.

Clinical and experimental allergy : journal of the British Society for Allergy and Clinical Immunology·2017
Same author

Common pattern of gray-matter abnormalities in drug-naive and medicated first-episode schizophrenia: a multimodal meta-analysis.

Psychological medicine·2016
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 Experiment Videos

Gradient-based residual variance modeling and its applications to motion-compensated video coding.

B Tao1, M T Orchard

  • 1Electrical Engineering Department, Princeton University, Princeton, NJ 08540, USA. bo.tao@streaming21.com

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|February 6, 2008
PubMed
Summary

This study shows that residual signal variance in video coding correlates with pixel gradient magnitude. This finding improves residual signal coding and enables faster block matching through gradient-adaptive subsampling.

Related Experiment Videos

Area of Science:

  • Video Coding
  • Digital Signal Processing
  • Image Analysis

Background:

  • Motion-compensated video coding relies on predicting and coding residual frames.
  • Understanding the statistical properties of residual signals is crucial for efficient coding.
  • Previous methods often assume stationary statistics for residual signals.

Purpose of the Study:

  • To analyze the relationship between residual signal variance and gradient magnitude in video coding.
  • To leverage this relationship for improved residual signal coding efficiency.
  • To develop a faster block matching algorithm using gradient-adaptive subsampling.

Main Methods:

  • Analysis of residual signal variance in relation to pixel gradient magnitude.
  • Non-stationary modeling of residual field second-order statistics.
  • Gradient-adaptive pixel subsampling for fast block matching.

Main Results:

  • Residual signal variance is directly dependent on gradient magnitude.
  • Larger gradient magnitudes correlate with higher residual signal variance.
  • Gradient-adaptive subsampling significantly outperforms existing methods in block matching.

Conclusions:

  • The relationship between residual variance and gradient magnitude offers a powerful tool for video coding optimization.
  • Non-stationary modeling enhances residual signal coding efficiency.
  • Gradient-adaptive subsampling provides a computationally efficient approach to fast block matching.