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Markerless 3D motion capture for animal locomotion studies [PDF]

Biology Open, 2014
Obtaining quantitative data describing the movements of animals is an essential step in understanding their locomotor biology. Outside the laboratory, measuring animal locomotion often relies on video-based approaches and analysis is hampered because of ...
William Irvin Sellers, Eishi Hirasaki
doaj   +3 more sources

Neural monocular 3D human motion capture with physical awareness [PDF]

ACM Transactions on Graphics, 2021
We present a new trainable system for physically plausible markerless 3D human motion capture, which achieves state-of-the-art results in a broad range of challenging scenarios. Unlike most neural methods for human motion capture, our approach, which we dub "physionical", is aware of physical and environmental constraints. It combines in a
Vladislav Golyanik, Weipeng Xu, Christian Theobalt   +2 more
exaly   +4 more sources

Evaluation of 3D Markerless Motion Capture Accuracy Using OpenPose With Multiple Video Cameras

Frontiers in Sports and Active Living, 2020
There is a need within human movement sciences for a markerless motion capture system, which is easy to use and sufficiently accurate to evaluate motor performance.
Nobuyasu Nakano, Nobuyasu Nakano, Tetsuro Sakura, Kazuhiro Ueda, Leon Omura, Leon Omura, Arata Kimura, Yoichi Iino, Senshi Fukashiro, Shinsuke Yoshioka   +9 more
doaj   +3 more sources

Accuracy, Validity, and Reliability of Markerless Camera-Based 3D Motion Capture Systems versus Marker-Based 3D Motion Capture Systems in Gait Analysis: A Systematic Review and Meta-Analysis

Sensors
(1) Background: Marker-based 3D motion capture systems (MBS) are considered the gold standard in gait analysis. However, they have limitations for which markerless camera-based 3D motion capture systems (MCBS) could provide a solution.
Sofia Scataglini, Eveline Abts, Cas Van Bocxlaer, Maxime Van den Bussche, Sara Meletani, Steven Truijen   +5 more
doaj   +3 more sources

Evaluating 3D Human Motion Capture on Mobile Devices

Applied Sciences, 2022
Computer-vision-based frameworks enable markerless human motion capture on consumer-grade devices in real-time. They open up new possibilities for application, such as in the health and medical sector.
Lara Marie Reimer, Maximilian Kapsecker, Takashi Fukushima, Stephan M. Jonas   +3 more
doaj   +1 more source

Using AI Motion Capture Systems to Capture Race Walking Technology at a Race Scene: A Comparative Experiment

Applied Sciences, 2022
Background: This study tested the reliability of the 3D coordinates of human joint points obtained by using an AI motion capture system at a race walking scene.
Dongtao Zhang, Zhongqiu Ji, Guiping Jiang, Weiwei Jiao   +3 more
doaj   +1 more source

Reliability and Concurrent Validity of a Markerless, Single Camera, Portable 3D Motion Capture System for Assessment of Glenohumeral Mobility.

International Journal of Sports Physical Therapy, 2023
# Introduction Recent technological advancements have enabled medical, sport, and fitness professionals to utilize digital tools that assist with conducting movement examinations and screenings.
Ofra Pottorf, Daniel Vapne, Jamie Ghigiarelli, Kaitlyn Haase   +3 more
doaj   +1 more source

Markerless motion capture of hands and fingers in high-speed throwing task and its accuracy verification

Mechanical Engineering Journal, 2023
In human motion capture systems, reflective markers attached to the body have been widely used to track motion using optical cameras. However, when the speed of motion increases, because the brightness and angle of view of the camera are limited, and the
Ayane KUSAFUKA, Naoki TSUKAMOTO, Kohei MIYATA, Kazutoshi KUDO   +3 more
doaj   +1 more source

A Complementary Filter Design on SE(3) to Identify Micro-Motions during 3D Motion Tracking

Sensors, 2020
In 3D motion capture, multiple methods have been developed in order to optimize the quality of the captured data. While certain technologies, such as inertial measurement units (IMU), are mostly suitable for 3D orientation estimation at relatively high ...
Gia-Hoang Phan, Clint Hansen, Paolo Tommasino, Asif Hussain, Domenico Formica, Domenico Campolo   +5 more
doaj   +1 more source

Early estimation model for 3D-discrete indian sign language recognition using graph matching

Journal of King Saud University: Computer and Information Sciences, 2021
Machine translation of sign language is a critical task of computer vision. In this work, we propose to use 3D motion capture technology for sign capture and graph matching for sign recognition.
E. Kiran Kumar, P.V.V. Kishore, D. Anil Kumar, M. Teja Kiran Kumar   +3 more
doaj   +1 more source