Sparse-Dense Motion Modelling and Tracking for Manipulation Without Prior Object Models-Reference-Cited by-同舟云学术

Sparse-Dense Motion Modelling and Tracking for Manipulation Without Prior Object Models

Published:2022-10 Issue:4 Volume:7 Page:11394-11401
ISSN:2377-3766
Container-title:IEEE Robotics and Automation Letters
language:
Short-container-title:IEEE Robot. Autom. Lett.

Author:

Rauch Christian¹^ORCID,Long Ran¹^ORCID,Ivan Vladimir¹^ORCID,Vijayakumar Sethu¹^ORCID

Affiliation:

1. School of Informatics, University of Edinburgh, Edinburgh, U.K.

Funder

EU H2020 Project Enhancing Healthcare with Assistive Robotic Mobile Manipulation

Alan Turing Institute

Kawada Robotics Corporation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Artificial Intelligence,Control and Optimization,Computer Science Applications,Computer Vision and Pattern Recognition,Mechanical Engineering,Human-Computer Interaction,Biomedical Engineering,Control and Systems Engineering

Link

http://xplorestaging.ieee.org/ielx7/7083369/9831196/09864140.pdf?arnumber=9864140

Reference20 articles.

1. 3D Object Reconstruction from Hand-Object Interactions

2. In-hand Object Scanning via RGB-D Video Segmentation

3. StaticFusion: Background Reconstruction for Dense RGB-D SLAM in Dynamic Environments

4. Co-fusion: Real-time segmentation, tracking and fusion of multiple objects

5. RigidFusion: Robot Localisation and Mapping in Environments With Large Dynamic Rigid Objects

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