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Thomas P. Andriacchi

Publications

Citations

Publications by Year

20072014

Co-Authors:

Ruzena BajcsyRama ChellappaChing-Hui ChenStefano CorazzaJulien Favre

Show All Co-Authors (8)

Thomas P. Andriacchi

Affiliation

Stanford University

Publication Topics

Motion Capture,
Body Segments,
Iterative Closest Point,
Joint Center,
Multiple Cameras,
2D Image Plane,
3D Mesh,
3D Point,
3D Reconstruction,
3D Representation,
3D Video,
Accurate Capture

Biography

Thomas P. Andriacchi is a professor in mechanical engineering and orthopedic surgery at Stanford University. His research interests include the biomechanics of human locomotion and its biomedical applications to artificial joints, sports injury, osteoarthritis, and neuromuscular disorders. Andriacchi received a PhD in mechanical engineering from the University of Illinois at Chicago. He is a Fellow of the American Society of Mechanical Engineers. Contact him at tandriac@stanford.edu.(Based on document published on 20 May 2014).

Publications

Citations

Publications by Year

20072014

Co-Authors:

Ruzena Bajcsy
Rama Chellappa
Ching-Hui Chen
Stefano Corazza
Julien Favre

Show All Co-Authors (8)

Author's Published Works

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Thomas P. Andriacchi(3)
Stefano Corazza(2)
Julien Favre(1)
Gregorij Kurillo(1)
Lars Mundermann(1)
University of Maryland(1)
University of California(1)
Department of Mechanical Engineering, University of Stanford, Stanford, CA, USA(1)
Biomotion Laboratory, Mechanical Engineering Department, University of Stanford, Stanford, CA, USA(1)
Stanford University(1)
2007 IEEE Conference on Computer Vision and Pattern Recognition(1)
Computer(1)
IEEE Transactions on Biomedical Engineering(1)
IEEE(3)
Minneapolis, MN, USA(1)
Motion Capture(3)
Body Segments(2)
Iterative Closest Point(2)
Joint Center(2)
Multiple Cameras(2)

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Camera Networks for Healthcare, Teleimmersion, and Surveillance

Ching-Hui Chen;Julien Favre;Gregorij Kurillo;Thomas P. Andriacchi;Ruzena Bajcsy;Rama Chellappa

Computer

Year: 2014 | Volume: 47, Issue: 5 | Magazine Article |

Cited by: Papers (8) | Patents (1)

HTML

Markerless technology is a game changer for motion-capture applications, such as the monitoring of patients outside the hospital, realistic face-to-face communication across continents, and observation across large spaces.Show More

Camera Networks for Healthcare, Teleimmersion, and Surveillance

Ching-Hui Chen;Julien Favre;Gregorij Kurillo;Thomas P. Andriacchi;Ruzena Bajcsy;Rama Chellappa

Computer

Year: 2014 | Volume: 47, Issue: 5 | Magazine Article |

Automatic Generation of a Subject-Specific Model for Accurate Markerless Motion Capture and Biomechanical Applications

Stefano Corazza;Emiliano Gambaretto;Lars Mündermann;Thomas P. Andriacchi

IEEE Transactions on Biomedical Engineering

Year: 2010 | Volume: 57, Issue: 4 | Journal Article |

Cited by: Papers (33)

HTML

A novel approach for the automatic generation of a subject-specific model consisting of morphological and joint location information is described. The aim is to address the need for efficient and accurate model generation for markerless motion capture (MMC) and biomechanical studies. The algorithm applied and expanded on previous work on human shapes space by embedding location information for te...Show More

Automatic Generation of a Subject-Specific Model for Accurate Markerless Motion Capture and Biomechanical Applications

Stefano Corazza;Emiliano Gambaretto;Lars Mündermann;Thomas P. Andriacchi

IEEE Transactions on Biomedical Engineering

Year: 2010 | Volume: 57, Issue: 4 | Journal Article |

Accurately measuring human movement using articulated ICP with soft-joint constraints and a repository of articulated models

Lars Mundermann;Stefano Corazza;Thomas P. Andriacchi

2007 IEEE Conference on Computer Vision and Pattern Recognition

Year: 2007 | Conference Paper |

Cited by: Papers (52) | Patents (2)

HTML

A novel approach for accurate markerless motion capture combining a precise tracking algorithm with a database of articulated models is presented. The tracking approach employs an articulated iterative closest point algorithm with soft-joint constraints for tracking body segments in visual hull sequences. The database of articulated models is derived from a combination of human shapes and anthropo...Show More

Accurately measuring human movement using articulated ICP with soft-joint constraints and a repository of articulated models

Lars Mundermann;Stefano Corazza;Thomas P. Andriacchi

2007 IEEE Conference on Computer Vision and Pattern Recognition

Year: 2007 | Conference Paper |

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