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

Geometric Mean01:15

Geometric Mean

4.0K
The mean is a measure of the central tendency of a data set. In some data sets, the data is inherently multiplicative, and the arithmetic mean is not useful. For example, the human population multiplies with time, and so does the credit amount of financial investment, as the interest compounds over successive time intervals.
In cases of multiplicative data, the geometric mean is used for statistical analysis. First, the product of all the elements is taken. Then, if there are n elements in the...
4.0K
Geometric Sequences01:30

Geometric Sequences

284
In systems where values diminish by a constant proportion at each stage, the resulting sequence follows a geometric structure. Each new value in the sequence is obtained by applying a fixed multiplier to the preceding term. This regular, proportional decline type is often used to represent processes involving gradual loss, such as energy dissipation or reduction in amplitude over time.When analyzing the total effect of such a process across unlimited iterations, the series of values is referred...
284
Chromatin Structure Regulates pre-mRNA Processing02:41

Chromatin Structure Regulates pre-mRNA Processing

8.2K
In eukaryotic cells, nascent mRNA transcripts need to undergo many post-transcriptional modifications to reach the cell cytoplasm and translate into functional proteins. For a long time, transcription and pre-mRNA processing were considered two independent events that occur sequentially in the cell. However, it has now been well established that transcription and pre-mRNA processing are two simultaneous processes that are precisely regulated inside the cell.
The chromatin structure, especially...
8.2K
Structures of Solids02:22

Structures of Solids

17.7K
Solids in which the atoms, ions, or molecules are arranged in a definite repeating pattern are known as crystalline solids. Metals and ionic compounds typically form ordered, crystalline solids. A crystalline solid has a precise melting temperature because each atom or molecule of the same type is held in place with the same forces or energy. Amorphous solids or non-crystalline solids (or, sometimes, glasses) which lack an ordered internal structure and are randomly arranged. Substances that...
17.7K
Additional Subnuclear Structures02:10

Additional Subnuclear Structures

5.4K
The eukaryotic nucleus is a double membrane-bound organelle that contains nearly all of the cell’s genetic material in the form of chromosomes. It is rightly called the “brain” of the cell as it shoulders the responsibility of responding to various physiological processes, stress, altered metabolic conditions, and other cellular signals. 
The nucleus contains many membrane-less subnuclear organelles or nuclear bodies, such as nucleoli, Cajal bodies, speckles,...
5.4K
Structural Isomerism02:34

Structural Isomerism

21.7K
Isomerism in Complexes
Isomers are different chemical species that have the same chemical formula. Structural isomerism of coordination compounds can be divided into two subcategories, the linkage isomers and coordination-sphere isomers.
Linkage isomers occur when the coordination compound contains a ligand that can bind to the transition metal center through two different atoms. For example, the CN− ligand can bind through the carbon atom or through the nitrogen atom. Similarly, SCN− can...
21.7K

You might also read

Related Articles

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

Sort by
Same author

A kinematic-geometric model based on ankles' depth trajectory in frontal plane for gait analysis using a single RGB-D camera.

Journal of biomechanics·2022
Same author

Rich Intrinsic Image Decomposition of Outdoor Scenes from Multiple Views.

IEEE transactions on visualization and computer graphics·2012
Same author

A hybrid multiview stereo algorithm for modeling urban scenes.

IEEE transactions on pattern analysis and machine intelligence·2012
Same author

Real-time rendering of rough refraction.

IEEE transactions on visualization and computer graphics·2011
Same author

Geometric feature extraction by a multimarked point process.

IEEE transactions on pattern analysis and machine intelligence·2010
Same author

A marked point process for modeling lidar waveforms.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2010
Same journal

Relation DETR+: Exploring Explicit Position Relation Prior for Dense Prediction.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

RBF++: Quantifying and Optimizing Reasoning Boundaries across Measurable and Unmeasurable Capabilities for Chain-of-Thought Reasoning.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

CAFE: Cross-View Adaptive Fusion and Cluster Center Enhancement for Robust Multi-View Clustering.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

DIVER: Reinforced Diffusion Breaks Imitation Bottlenecks in End-to-End Autonomous Driving.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

Ethics-Aware Safe Reinforcement Learning for Rare-Event Risk Control in Interactive Urban Driving.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

Learning Shape Anchors for Holistic Indoor Scene Understanding.

IEEE transactions on pattern analysis and machine intelligence·2026
See all related articles

Related Experiment Video

Updated: Jan 31, 2026

One-Step Approach to Fabricating Polydimethylsiloxane Microfluidic Channels of Different Geometric Sections by Sequential Wet Etching Processes
08:31

One-Step Approach to Fabricating Polydimethylsiloxane Microfluidic Channels of Different Geometric Sections by Sequential Wet Etching Processes

Published on: September 13, 2018

10.4K

Extracting Geometric Structures in Images with Delaunay Point Processes.

Jean-Dominique Favreau, Florent Lafarge, Adrien Bousseau

    IEEE Transactions on Pattern Analysis and Machine Intelligence
    |January 4, 2019
    PubMed
    Summary
    This summary is machine-generated.

    We present Delaunay Point Processes, a novel framework for extracting geometric structures from images. This method efficiently identifies and connects image features, improving geometric analysis tasks.

    More Related Videos

    Automatic Image Processing to Determine the Community Size Structure of Riverine Macroinvertebrates
    08:56

    Automatic Image Processing to Determine the Community Size Structure of Riverine Macroinvertebrates

    Published on: January 13, 2023

    2.9K
    Uncovering Hidden Dynamics of Natural Photonic Structures Using Holographic Imaging
    05:45

    Uncovering Hidden Dynamics of Natural Photonic Structures Using Holographic Imaging

    Published on: March 31, 2022

    3.1K

    Related Experiment Videos

    Last Updated: Jan 31, 2026

    One-Step Approach to Fabricating Polydimethylsiloxane Microfluidic Channels of Different Geometric Sections by Sequential Wet Etching Processes
    08:31

    One-Step Approach to Fabricating Polydimethylsiloxane Microfluidic Channels of Different Geometric Sections by Sequential Wet Etching Processes

    Published on: September 13, 2018

    10.4K
    Automatic Image Processing to Determine the Community Size Structure of Riverine Macroinvertebrates
    08:56

    Automatic Image Processing to Determine the Community Size Structure of Riverine Macroinvertebrates

    Published on: January 13, 2023

    2.9K
    Uncovering Hidden Dynamics of Natural Photonic Structures Using Holographic Imaging
    05:45

    Uncovering Hidden Dynamics of Natural Photonic Structures Using Holographic Imaging

    Published on: March 31, 2022

    3.1K

    Area of Science:

    • Computer Vision
    • Computational Geometry
    • Image Analysis

    Background:

    • Traditional point processes struggle with modeling interconnected geometric structures in images.
    • Extracting complex geometric primitives like line networks and polygons requires robust methods.

    Purpose of the Study:

    • To introduce Delaunay Point Processes (DPP) as a unified framework for geometric structure extraction from images.
    • To develop an efficient method for simultaneously locating and grouping geometric primitives into extended structures.
    • To leverage Delaunay triangulation for improved connectivity and computational efficiency in image analysis.

    Main Methods:

    • Utilizing Markov Chain Monte Carlo (MCMC) to minimize an energy function balancing image data fidelity and geometric priors.
    • Embedding a point process within a Delaunay triangulation to ensure inherent high-quality connectivity.
    • Developing a fast MCMC sampler by exploiting the properties of Delaunay triangulations.

    Main Results:

    • Demonstrated the framework's ability to extract interconnected geometric structures like line networks and polygons.
    • Achieved efficient simultaneous localization and grouping of geometric primitives.
    • Successfully applied the method to diverse applications including line network extraction, object contouring, and mesh-based image compression.

    Conclusions:

    • Delaunay Point Processes offer a flexible and powerful framework for geometric structure extraction in images.
    • The integration of Delaunay triangulation significantly enhances the modeling of connected components and sampler efficiency.
    • The proposed method shows broad applicability across various image analysis tasks, outperforming traditional approaches for complex structures.