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

Ranks01:02

Ranks

Unlike parametric methods, nonparametric statistics are ideal for nominal and ordinal data, requiring fewer assumptions about the population's nature or distribution. This makes nonparametric methods easier to apply and interpret, as they do not depend on parameters like mean or standard deviation. One common approach in nonparametric analysis is to sort data according to a specific criterion. For instance, we might arrange weather data from hottest to coldest days in a month or rank cities...
Quantifying and Rejecting Outliers: The Grubbs Test01:02

Quantifying and Rejecting Outliers: The Grubbs Test

Sometimes, a data set can have a recorded numerical observation that greatly  deviates from the rest of the data. Assuming that the data is normally distributed, a statistical method called the Grubbs test can be used to determine whether the observation is truly an outlier.  To perform a two-tailed Grubbs test, first, calculate the absolute difference between the outlier and the mean. Then, calculate the ratio between this difference and the standard deviation of the sample. This number is...
Friedman Two-way Analysis of Variance by Ranks01:21

Friedman Two-way Analysis of Variance by Ranks

Friedman's Two-Way Analysis of Variance by Ranks is a nonparametric test designed to identify differences across multiple test attempts when traditional assumptions of normality and equal variances do not apply. Unlike conventional ANOVA, which requires normally distributed data with equal variances, Friedman's test is ideal for ordinal or non-normally distributed data, making it particularly useful for analyzing dependent samples, such as matched subjects over time or repeated measures from...
Wilcoxon Rank-Sum Test01:21

Wilcoxon Rank-Sum Test

The Wilcoxon rank-sum test, also known as the Mann-Whitney U test, is a nonparametric test used to determine if there is a significant difference between the distributions of two independent samples. This test is designed specifically for two independent populations and has the following key requirements:
Aggregates Classification01:29

Aggregates Classification

Aggregate classification is generally based on its size, petrographic characteristics, weight, and source. Size classification ranges from coarse to fine aggregates, defined by the size of the particles. Coarse aggregates are particles that do not pass through ASTM sieve No. 4, and aggregates that pass through the sieve are fine aggregates.
Petrographic classification groups aggregates based on common mineralogical characteristics. Some of the common mineral groups found in aggregates are...
Routh-Hurwitz Criterion II01:19

Routh-Hurwitz Criterion II

In the application of the Routh-Hurwitz criterion, two specific scenarios can arise that complicate stability analysis.
The first scenario occurs when a singular zero appears in the first column of the Routh table. This situation creates a division by zero issues. To resolve this, a small positive or negative number, denoted as epsilon (∈), is substituted for the zero. The stability analysis proceeds by assuming a sign for ∈. If ∈ is positive, any sign change in the first column of the Routh...

You might also read

Related Articles

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

Sort by
Same author

Bacillus amyloliquefaciens PDR1 from root of karst adaptive plant enhances Arabidopsis thaliana resistance to alkaline stress through modulation of plasma membrane H<sup>+</sup>-ATPase activity.

Plant physiology and biochemistry : PPB·2020
Same author

Integrative analyses of single-cell transcriptome and regulome using MAESTRO.

Genome biology·2020
Same author

Monitoring bronchoalveolar lavage with electrical impedance tomography: first experience in a patient with COVID-19.

Physiological measurement·2020
Same author

The genome sequence of the grape phylloxera provides insights into the evolution, adaptation, and invasion routes of an iconic pest.

BMC biology·2020
Same author

An Acoustic Meta-Skin Insulator.

Advanced materials (Deerfield Beach, Fla.)·2020
Same author

Sparse representation of Brillouin spectrum using dictionary learning.

Optics express·2020
Same journal

Change-Prior-Guided Unsupervised Change Detection of Heterogeneous Remote Sensing Images.

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

AgonicDreamer: Enhancing Multi-View Consistency in Text-to-3D Generation via Rectified Score Distillation.

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

BiCM-Prompt: Bidirectional Cross-Modal Prompt Tuning for Class-Incremental Learning on Multisource Remote Sensing Images.

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

GoP-based Quality Enhancement on Video Compression.

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

Align then Tensorize: Multi-Level Consistent Anchor Graph Learning for Scalable Multi-View Clustering.

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

Beyond Fidelity: Diverse Image Synthesis via Retrieval-Augmented Diffusion.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
See all related articles

Related Experiment Video

Updated: May 24, 2026

Utilizing vmTracking to Improve the Accuracy of Multi-Animal Pose Estimation in Rodent Social Behavior Studies
07:34

Utilizing vmTracking to Improve the Accuracy of Multi-Animal Pose Estimation in Rodent Social Behavior Studies

Published on: November 7, 2025

Robust tracking with discriminative ranking lists.

Ming Tang1, Xi Peng

  • 1Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China. tangm@nlpr.ia.ac.cn

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|March 6, 2012
PubMed
Summary
This summary is machine-generated.

This study introduces the discriminative ranking list-based tracker (DRLTracker), a novel algorithm for object tracking. DRLTracker effectively handles distractions by modeling objects and backgrounds using ranked patch lists, outperforming existing methods.

Related Experiment Videos

Last Updated: May 24, 2026

Utilizing vmTracking to Improve the Accuracy of Multi-Animal Pose Estimation in Rodent Social Behavior Studies
07:34

Utilizing vmTracking to Improve the Accuracy of Multi-Animal Pose Estimation in Rodent Social Behavior Studies

Published on: November 7, 2025

Area of Science:

  • Computer Vision
  • Machine Learning
  • Artificial Intelligence

Background:

  • Object tracking is crucial in computer vision.
  • Existing trackers struggle with target distraction and scale variations.
  • Robust modeling of target objects and backgrounds is needed.

Purpose of the Study:

  • To propose a novel object tracking algorithm, the discriminative ranking list-based tracker (DRLTracker).
  • To enhance tracking robustness by effectively modeling target objects and local backgrounds.
  • To address the distraction problem in object tracking.

Main Methods:

  • The DRLTracker utilizes ranking lists of image patches at different scales.
  • Object models are formed using high-purity patches and confusable background patches.
  • A collaborative approach using multi-scale object models predicts target location in subsequent frames.

Main Results:

  • The DRLTracker demonstrates superior performance compared to representative and state-of-the-art trackers.
  • Extensive experiments validate the algorithm's effectiveness in alleviating distraction problems.
  • The algorithm shows robust tracking capabilities across various challenging scenarios.

Conclusions:

  • The proposed DRLTracker offers an effective solution for object tracking, particularly in scenarios prone to distraction.
  • The ranking list-based modeling approach provides a robust mechanism for target representation.
  • DRLTracker represents a significant advancement in the field of visual object tracking.