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 Experiment Video

Updated: May 23, 2026

Estimation of Contact Regions Between Hands and Objects During Human Multi-Digit Grasping
09:41

Estimation of Contact Regions Between Hands and Objects During Human Multi-Digit Grasping

Published on: April 21, 2023

Human pose co-estimation and applications.

Marcin Eichner1, Vittorio Ferrari

  • 1ETH Zurich, Computer Vision Laboratory, Zurich, Switzerland. eichner@vision.ee.ethz.ch

IEEE Transactions on Pattern Analysis and Machine Intelligence
|April 11, 2012
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

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

Sort by
Same author

Objective Assessment of Visual Workload in Video Display Terminal Workers Using a Non-Invasive Monitoring System.

La Medicina del lavoro·2026
Same author

Fertility preservation in prepubertal boys: management and follow-up challenges.

Endocrine connections·2026
Same author

Endocrine Late Effects of Targeted and Immune-Based Therapies in Pediatric Oncology.

Cells·2026
Same author

A MEMS Variable Reluctance Sensor for Contactless Detection of a Ferrous Rotating Target.

Sensors (Basel, Switzerland)·2026
Same author

Changes in Coping Strategies of Parents and Girls with Central Precocious Puberty Before and After the COVID-19 Lockdown: Data from Four Italian Pediatric Endocrinology Centers.

International journal of environmental research and public health·2025
Same author

Puberty, but not precocious puberty is influenced by weight gain in the first years of life.

Endocrine·2025
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

Human Pose Coestimation (PCE) jointly estimates multiple people's poses and learns shared pose prototypes. This approach improves accuracy for synchronized activities and learning poses from image searches.

Area of Science:

  • Computer Vision
  • Machine Learning
  • Artificial Intelligence

Background:

  • Existing Human Pose Estimation (HPE) methods often process individuals independently.
  • This can be suboptimal when multiple people share a common, underlying pose structure.

Purpose of the Study:

  • Introduce Human Pose Coestimation (PCE) for joint pose estimation and prototype learning.
  • Demonstrate PCE's effectiveness in improving pose estimation accuracy and learning meaningful pose priors.

Main Methods:

  • Developed a novel Human Pose Coestimation (PCE) framework.
  • Applied PCE to synchronized group activities (aerobics, dancing) and learning from image search engine queries (e.g., "lotus pose").

Main Results:

Related Experiment Videos

Last Updated: May 23, 2026

Estimation of Contact Regions Between Hands and Objects During Human Multi-Digit Grasping
09:41

Estimation of Contact Regions Between Hands and Objects During Human Multi-Digit Grasping

Published on: April 21, 2023

  • PCE significantly improves pose estimation accuracy compared to independent estimation methods.
  • Learned meaningful prototype poses from image search results, serving as effective priors for novel pose estimation.

    • Conclusions:

    • Jointly estimating poses and learning prototypes simplifies the problem and enhances accuracy.
    • PCE offers a powerful approach for analyzing group activities and learning pose representations from large-scale, uncurated data.