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

Distance Problem01:29

Distance Problem

When an object's velocity changes over time, the total distance traveled can be determined by summing small displacement intervals over short increments. This approach approximates the true distance through numerical summation and the use of integral calculus. An estimate of the total displacement can be obtained by measuring velocity at regular intervals and multiplying each value by the corresponding time step.If a runner accelerates over the first three seconds of a race, speed measurements...
Relative Velocity in One Dimension01:10

Relative Velocity in One Dimension

The understanding of the concept of reference frames is essential to discuss relative motion in one or more dimensions. When we say that an object has a certain velocity, we must state the velocity with respect to a given reference frame. In most examples, this reference frame has been Earth. For instance, if a statement reads that a person is sitting in a train moving at 10 m/s east, then it implies that the person on the train is moving relative to the surface of Earth at this velocity,...
Causes of Similarity-Dissimilarity Effect01:26

Causes of Similarity-Dissimilarity Effect

The similarity-dissimilarity effect, a fundamental concept in social psychology, explains how interpersonal similarities and differences influence attraction and social interactions. This effect is supported by three key psychological perspectives: balance theory, social comparison theory, and consensual validation.Balance Theory and Cognitive ConsistencyBalance theory, developed by Fritz Heider, posits that individuals seek cognitive consistency in their relationships. When two people share...
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 Risk01:12

Relative Risk

Relative risk (RR) is a statistical measure commonly used in epidemiology to compare the likelihood of a particular event occurring between two groups. This metric is important for evaluating the relationship between exposure to a specific risk factor and the probability of a particular outcome. It plays a crucial role in medical research, public health studies, and risk assessment. Relative risk quantifies how much more (or less) likely an event is to occur in an exposed group compared to an...
Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...

You might also read

Related Articles

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

Sort by
Same author

A molybdenum-promoted nickel-aluminum alloy catalyst for high-efficient hydrogenation reduction of nitrate to ammonia and nitrogen.

RSC advances·2026
Same author

Molecular Glues Recruiting RNF213 As an E3 Ligase for Targeted Protein Degradation: A Minimal Dibromoacetamide Warhead As a Recruitment Ligand.

Journal of the American Chemical Society·2026
Same author

Solving the Hubbard model with neural quantum states.

Nature communications·2026
Same author

Pyroptosis-immunity-microbiome axis in acute upper gastrointestinal bleeding: mechanisms, risk prediction, and individualized strategies.

Frontiers in medicine·2026
Same author

The Analgesic Efficacy and Safety of Intramuscular Hydromorphone Versus Butorphanol for Acute Pain in the Emergency Department: A Randomized Trial.

Pain research & management·2026
Same author

XOV-Action: Towards Generalizable Open-Vocabulary Action Recognition.

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

Benchmarking the Robustness of Autonomous Driving to Environmental Illusions: A Lane Perception Perspective.

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

Learning Topology-Aware Representations via Test-Time Adaptation for Anomaly Segmentation.

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

TraGraph-GS: Trajectory Graph-based Gaussian Splatting for Arbitrary Large-Scale Scene Rendering.

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

SWIFT: A Small-World Interaction Framework for Flow-Aware Trajectory Prediction in Autonomous Driving.

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

HardFlow: Hard-Constrained Sampling for Flow-Matching Models Via Trajectory Optimization.

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

Industrial Brain: Self-Evolving Neuro-Symbolic Autonomy with Causal Resilience for Cyber-Physical Systems.

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

Related Experiment Video

Updated: May 21, 2026

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
08:12

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

Published on: March 1, 2022

Reidentification by Relative Distance Comparison.

Wei-Shi Zheng, Shaogang Gong, Tao Xiang

    IEEE Transactions on Pattern Analysis and Machine Intelligence
    |June 27, 2012
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces a novel relative distance comparison (RDC) learning method for person reidentification. The RDC model improves matching accuracy across different camera views and times, outperforming existing techniques.

    Related Experiment Videos

    Last Updated: May 21, 2026

    A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
    08:12

    A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

    Published on: March 1, 2022

    Area of Science:

    • Computer Vision
    • Machine Learning
    • Pattern Recognition

    Background:

    • Person reidentification (re-ID) is crucial for tracking individuals across non-overlapping camera views over time.
    • Challenges in re-ID include significant visual appearance variations due to viewpoint, lighting, occlusion, and background clutter.
    • Existing methods often struggle with finding robust similarity measures for diverse features under realistic conditions.

    Purpose of the Study:

    • To address the limitations of current person reidentification techniques by developing a superior similarity measure.
    • To formulate person reidentification as a relative distance comparison (RDC) learning problem.
    • To introduce a novel RDC model that learns an optimal similarity measure for person images.

    Main Methods:

    • Formulated person reidentification as a relative distance comparison (RDC) learning problem.
    • Introduced a novel RDC model designed to maximize the likelihood of true matches having smaller distances than false matches.
    • Developed an ensemble RDC model for improved scalability and tractability in large-scale learning.

    Main Results:

    • The proposed RDC models demonstrated clear superiority over popular person reidentification techniques on three benchmark datasets.
    • The RDC models showed enhanced robustness against visual appearance changes.
    • The new models were less susceptible to model overfitting compared to existing methods.

    Conclusions:

    • Relative distance comparison learning offers a promising approach for robust person reidentification.
    • The developed RDC models provide an effective solution for the challenging problem of matching people across diverse visual conditions.
    • The RDC approach advances the field by learning optimal similarity measures rather than relying on pre-defined features.