Jove
Visualize
Contact Us

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

Revealing the Hidden Social Structure of Pigs with AI-Assisted Automated Monitoring Data and Social Network Analysis.

Animals : an open access journal from MDPI·2025
Same author

Estimating genetic parameters of digital behavior traits and their relationship with production traits in purebred pigs.

Genetics, selection, evolution : GSE·2024
Same author

Software JimenaE allows efficient dynamic simulations of Boolean networks, centrality and system state analysis.

Scientific reports·2023
Same author

Evaluation of a novel computer vision-based livestock monitoring system to identify and track specific behaviors of individual nursery pigs within a group-housed environment.

Translational animal science·2022
Same author

Population-Predicted MHC Class II Epitope Presentation of SARS-CoV-2 Structural Proteins Correlates to the Case Fatality Rates of COVID-19 in Different Countries.

International journal of molecular sciences·2021
Same author

End-Effector Contact and Force Detection for Miniature Autonomous Robots Performing Lunar and Expeditionary Surgery.

Military medicine·2021
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 14, 2026

Design and Fabrication of an Elastomeric Unit for Soft Modular Robots in Minimally Invasive Surgery
11:06

Design and Fabrication of an Elastomeric Unit for Soft Modular Robots in Minimally Invasive Surgery

Published on: November 14, 2015

Stereoscopic vision-based robotic manipulator extraction method for enhanced soft tissue reconstruction.

Jędrzej Kowalczuk1, Eric Psota, Lance C Pérez

  • 1Department of Electrical Engineering, University of Nebraska-Lincoln, NE, USA.

Studies in Health Technology and Informatics
|February 13, 2013
PubMed
Summary

This study presents a computer vision method to accurately identify surgical robotic arms in 3D operating room views. This technique enhances 3D reconstruction and augmented reality applications in robotic surgery.

More Related Videos

Robotized Testing of Camera Positions to Determine Ideal Configuration for Stereo 3D Visualization of Open-Heart Surgery
05:12

Robotized Testing of Camera Positions to Determine Ideal Configuration for Stereo 3D Visualization of Open-Heart Surgery

Published on: August 12, 2021

Design and Implementation of a Bespoke Robotic Manipulator for Extra-corporeal Ultrasound
07:41

Design and Implementation of a Bespoke Robotic Manipulator for Extra-corporeal Ultrasound

Published on: January 7, 2019

Related Experiment Videos

Last Updated: May 14, 2026

Design and Fabrication of an Elastomeric Unit for Soft Modular Robots in Minimally Invasive Surgery
11:06

Design and Fabrication of an Elastomeric Unit for Soft Modular Robots in Minimally Invasive Surgery

Published on: November 14, 2015

Robotized Testing of Camera Positions to Determine Ideal Configuration for Stereo 3D Visualization of Open-Heart Surgery
05:12

Robotized Testing of Camera Positions to Determine Ideal Configuration for Stereo 3D Visualization of Open-Heart Surgery

Published on: August 12, 2021

Design and Implementation of a Bespoke Robotic Manipulator for Extra-corporeal Ultrasound
07:41

Design and Implementation of a Bespoke Robotic Manipulator for Extra-corporeal Ultrasound

Published on: January 7, 2019

Area of Science:

  • Robotics
  • Computer Vision
  • Surgical Technology

Background:

  • Digital stereoscopic video feedback on surgical robotic platforms enables advanced computer vision applications.
  • Accurate identification of robotic manipulators is crucial for enhancements like augmented reality and semi-automated surgery.

Purpose of the Study:

  • To present a novel method for extracting robotic manipulators from stereoscopic surgical video feeds.
  • To demonstrate the method's accuracy in identifying manipulator locations.
  • To show the method's utility in improving 3D reconstruction and augmented views.

Main Methods:

  • Combines marker tracking, inverse kinematics, and computer rendering.
  • Processes stereoscopic video feedback from surgical robotic platforms.
  • Applies computer vision techniques to the operating field.

Main Results:

  • The method accurately identifies the locations of robotic manipulators within stereoscopic views.
  • Demonstrated enhancement of 3D reconstruction of the surgical environment.
  • Successful production of augmented reality views using the identified manipulator data.

Conclusions:

  • The presented method effectively extracts robotic manipulators from surgical video.
  • This technique offers significant potential for improving augmented reality and semi-automated surgical procedures.
  • Enhances visualization and data for advanced robotic surgery applications.