Jove
Visualize
Contact Us
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 Concept Videos

Carbon Skeletons01:12

Carbon Skeletons

115.4K
Life on Earth is carbon-based, as all macromolecules that make up living organisms contain carbon atoms. All organic compounds have a carbon backbone. Each carbon atom is tetravalent and can bond with four other atoms, making it an extraordinarily flexible component of biological molecules. Because carbon’s valence electrons are stable, it rarely becomes an ion. As the carbon chain increases in length, structural modifications such as ring structures, double bonds, and branching side...
115.4K
Coordination Number and Geometry02:57

Coordination Number and Geometry

19.1K
For transition metal complexes, the coordination number determines the geometry around the central metal ion. Table 1 compares coordination numbers to molecular geometry. The most common structures of the complexes in coordination compounds are octahedral, tetrahedral, and square planar.
19.1K
Predicting Molecular Geometry02:27

Predicting Molecular Geometry

46.0K
VSEPR Theory for Determination of Electron Pair Geometries
46.0K
Geometry of Hyperbolas01:30

Geometry of Hyperbolas

510
A hyperbola consists of all points where the absolute difference of distances to two fixed points, called foci, remains constant. The standard equation isEach branch extends infinitely and approaches two asymptotes, which guide the curve’s behavior. The parameters a and b define key features: a measures the distance from the center to each vertex along the transverse axis, while b influences the slopes of the asymptotes. The asymptotes have equationsA rectangle centered at the origin with...
510
Fixed Action Patterns01:06

Fixed Action Patterns

17.7K
A fixed action pattern (FAP) is a specific, hard-wired sequence of behaviors that occurs in response to an external stimulus, called a sign stimulus. The behavior is “fixed” because it is essentially unchangeable—proceeding similarly across individuals of a species every time it occurs.
17.7K
State Space Representation01:27

State Space Representation

593
The frequency-domain technique, commonly used in analyzing and designing feedback control systems, is effective for linear, time-invariant systems. However, it falls short when dealing with nonlinear, time-varying, and multiple-input multiple-output systems. The time-domain or state-space approach addresses these limitations by utilizing state variables to construct simultaneous, first-order differential equations, known as state equations, for an nth-order system.
Consider an RLC circuit, a...
593

You might also read

Related Articles

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

Sort by
Same author

Location Matters: Frequency-Spatial Dual-Space Adaptation for Cross-Domain Few-Shot Segmentation.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same author

Data-Free Class-Incremental Gesture Recognition With Prototype-Guided Pseudo-Feature Replay.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same author

Deciphering microbial dynamics in coastal ecosystems under polycyclic aromatic hydrocarbon stress: Community assembly, interaction networks, and metabolic adaptations.

Environmental research·2025
Same author

Foundation Model for Skeleton-Based Human Action Understanding.

IEEE transactions on pattern analysis and machine intelligence·2025
Same author

Localization and recognition of human action in 3D using transformers.

Communications engineering·2024
Same author

Addressing Skewed Heterogeneity via Federated Prototype Rectification With Personalization.

IEEE transactions on neural networks and learning systems·2024

Related Experiment Video

Updated: Feb 9, 2026

Quantifying Learning in Young Infants: Tracking Leg Actions During a Discovery-learning Task
11:18

Quantifying Learning in Young Infants: Tracking Leg Actions During a Discovery-learning Task

Published on: June 1, 2015

11.2K

Beyond Joints: Learning Representations From Primitive Geometries for Skeleton-Based Action Recognition and

Hongsong Wang, Liang Wang

    IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
    |June 6, 2018
    PubMed
    Summary

    This study introduces a new method for skeleton-based action recognition using joints, edges, and surfaces. The approach significantly improves performance on large datasets for both action recognition and detection tasks.

    More Related Videos

    Novel Object Recognition Test for the Investigation of Learning and Memory in Mice
    08:52

    Novel Object Recognition Test for the Investigation of Learning and Memory in Mice

    Published on: August 30, 2017

    77.6K
    Asthma Detection Research Based on Voice Signal Processing and Machine Learning
    04:04

    Asthma Detection Research Based on Voice Signal Processing and Machine Learning

    Published on: July 22, 2025

    1.0K

    Related Experiment Videos

    Last Updated: Feb 9, 2026

    Quantifying Learning in Young Infants: Tracking Leg Actions During a Discovery-learning Task
    11:18

    Quantifying Learning in Young Infants: Tracking Leg Actions During a Discovery-learning Task

    Published on: June 1, 2015

    11.2K
    Novel Object Recognition Test for the Investigation of Learning and Memory in Mice
    08:52

    Novel Object Recognition Test for the Investigation of Learning and Memory in Mice

    Published on: August 30, 2017

    77.6K
    Asthma Detection Research Based on Voice Signal Processing and Machine Learning
    04:04

    Asthma Detection Research Based on Voice Signal Processing and Machine Learning

    Published on: July 22, 2025

    1.0K

    Area of Science:

    • Computer Vision
    • Machine Learning
    • Artificial Intelligence

    Background:

    • Skeleton-based action recognition is advancing due to better sensors and pose estimation.
    • Traditional methods struggle with large datasets due to limited feature representation.
    • Existing recurrent neural network (RNN) methods often overlook geometric relationships between body joints.

    Purpose of the Study:

    • To leverage geometric relationships among joints for improved action recognition.
    • To develop a unified network capable of processing joints, edges, and surfaces for action recognition.
    • To enhance action detection using a novel multi-scale sliding window algorithm.

    Main Methods:

    • Introduced three primitive geometries: joints, edges, and surfaces.
    • Designed an end-to-end recurrent neural network (RNN) to process these geometric inputs.
    • Incorporated a viewpoint transformation layer and temporal dropout layers for robust representation learning.
    • Employed frame-wise action classification followed by a multi-scale sliding window for action detection.

    Main Results:

    • Demonstrated the effectiveness and complementarity of joints, edges, and surfaces across different actions.
    • Achieved state-of-the-art performance on large-scale 3D action recognition benchmark datasets.
    • Significantly outperformed existing methods in both action recognition and action detection tasks.

    Conclusions:

    • Geometric information (joints, edges, surfaces) is crucial for robust skeleton-based action recognition.
    • The proposed RNN-based network effectively utilizes geometric features for superior performance.
    • The developed methods represent a significant advancement in both action recognition and detection.