Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

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....

Deconvolution

Deconvolution

Deconvolution, also known as inverse filtering, is the process of extracting the impulse response from known input and output signals. This technique is vital in scenarios where the system's characteristics are unknown, and they must be inferred from the observable signals.
Deconvolution involves several mathematical techniques to derive the impulse response. One common approach is polynomial division. In this method, the input and output sequences are treated as coefficients of...

Convolution: Math, Graphics, and Discrete Signals

Convolution: Math, Graphics, and Discrete Signals

In any LTI (Linear Time-Invariant) system, the convolution of two signals is denoted using a convolution operator, assuming all initial conditions are zero. The convolution integral can be divided into two parts: the zero-input or natural response and the zero-state or forced response, with t0 indicating the initial time.
To simplify the convolution integral, it is assumed that both the input signal and impulse response are zero for negative time values. The graphical convolution process...

Convolution Properties II

Convolution Properties II

The important convolution properties include width, area, differentiation, and integration properties.
The width property indicates that if the durations of input signals are T1 and T2, then the width of the output response equals the sum of both durations, irrespective of the shapes of the two functions. For instance, convolving two rectangular pulses with durations of 2 seconds and 1 second results in a function with a width of 3 seconds.
The area property asserts that the area under the...

Linear Approximation in Time Domain

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,...

Reducing Line Loss

Reducing Line Loss

In a three-phase circuit, line loss is an indicator of energy dissipated as heat due to the resistance of transmission lines. To address this, incorporating transformers into the system—a step-up transformer at the source and a step-down transformer at the load—is a strategic solution. Two three-phase transformers are introduced to improve this.
With a step-up transformer at the source, the voltage is increased, thereby reducing the current in the transmission lines since power loss...

You might also read

Related Articles

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

Sort by

Same author

Synergistic bactericidal mechanism of carvacrol and ε-polylysine against <i>Staphylococcus aureus</i>: dysregulation of cellular homeostasis and metabolism.

RSC advances·2026

Same author

Tinengotinib (TT-00420) inhibits tumor growth and overcomes multidrug resistance in gastrointestinal cancers.

Molecular cancer therapeutics·2026

Same author

Diagenesis and Petroleum Significance of Veins in Marine Carbonate: A Case Study from the Subsalt Ordovician Fourth Member of the Majiagou Formation, Ordos Basin, China.

ACS omega·2026

Same author

Publisher Correction: Exosome-mediated Piezo1 activation in 3D-printed titanium scaffolds promotes repair of femoral head osteonecrosis.

Journal of nanobiotechnology·2026

Same author

Breaking the Diffraction-Encoding Limit for High-Capacity Meta-Holography via Multiorder Decoupling.

ACS nano·2026

Same author

Synergistic heterotrophic-photomixotrophic cultivation enhances fucoxanthin production in Poterioochromonas malhamensis (golden microalga).

Bioresource technology·2026

Search research articles

Related Experiment Video

Updated: Oct 5, 2025

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

Graph Convolutional Dictionary Selection With L₂_,ₚ Norm for Video Summarization.

Mingyang Ma, Shaohui Mei, Shuai Wan

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

|January 31, 2022

Summary

This study introduces a novel graph convolutional dictionary selection framework for video summarization. It effectively addresses redundancy and incorporates structured information for improved keyframe and shot selection.

More Related Videos

Deep Neural Networks for Image-Based Dietary Assessment

Deep Neural Networks for Image-Based Dietary Assessment

Published on: March 13, 2021

Author Spotlight: Assessment of Visual Acuity in Central Vision Loss Through Motion-Based Peripheral Vision Testing

Author Spotlight: Assessment of Visual Acuity in Central Vision Loss Through Motion-Based Peripheral Vision Testing

Published on: February 23, 2024

Related Experiment Videos

Last Updated: Oct 5, 2025

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

Deep Neural Networks for Image-Based Dietary Assessment

Deep Neural Networks for Image-Based Dietary Assessment

Published on: March 13, 2021

Author Spotlight: Assessment of Visual Acuity in Central Vision Loss Through Motion-Based Peripheral Vision Testing

Author Spotlight: Assessment of Visual Acuity in Central Vision Loss Through Motion-Based Peripheral Vision Testing

Published on: February 23, 2024

Area of Science:

Computer Science
Artificial Intelligence
Machine Learning

Background:

Video Summarization (VS) aids in understanding large video datasets.
Dictionary selection with sparse regularization is a promising VS approach.
Existing models neglect video frame structure and suffer from keyframe redundancy.

Purpose of the Study:

To propose a general framework, Graph Convolutional Dictionary Selection with L2,p norm (GCDS2,p), for video summarization.
To address limitations of existing methods by incorporating structured information and improving sparsity.
To enable both keyframe selection and skimming-based summarization.

Main Methods:

Incorporating graph embedding into dictionary selection to create a graph embedding dictionary.
Utilizing L2,p norm constrained row sparsity for flexible summarization.
Developing an efficient iterative algorithm with theoretically proven convergence.

Main Results:

The proposed GCDS2,p framework effectively selects diverse and representative keyframes.
The method successfully identifies key shots for skimming-based summarization.
Experimental results on benchmark datasets demonstrate superior performance.

Conclusions:

GCDS2,p offers an effective solution for video summarization by leveraging structured information and advanced sparsity.
The framework provides flexibility for both keyframe selection and skimming.
The proposed method outperforms existing approaches in video summarization tasks.