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ZMP Trajectory from Human Body Locomotion Dynamics Evaluated by Kinect-based Motion Capture System

Topics: Active and Robot Vision; Device Calibration, Characterization and Modeling; Image Formation, Acquisition Devices and Sensors; Image-Based Modeling and 3D Reconstruction; Multimodal and Multi-Sensor Models of Image Formation; Stereo Vision and Structure from Motion; Vision for Robotics

Authors: Igor Danilov ; Bulat Gabbasov ; Ilya Afanasyev and Evgeni Magid

Affiliation: Innopolis University, Russian Federation

ISBN: 978-989-758-175-5

Keyword(s): Motion Capture (MoCap), Zero Moment Point (ZMP), Kinect Sensor, Biomechanical Analysis of Human Locomotion, Multi-depth Sensor Video Recording.

Related Ontology Subjects/Areas/Topics: Active and Robot Vision ; Applications ; Computer Vision, Visualization and Computer Graphics ; Device Calibration, Characterization and Modeling ; Geometry and Modeling ; Image Formation and Preprocessing ; Image Formation, Acquisition Devices and Sensors ; Image-Based Modeling ; Motion, Tracking and Stereo Vision ; Multimodal and Multi-Sensor Models of Image Formation ; Pattern Recognition ; Robotics ; Software Engineering ; Stereo Vision and Structure from Motion

Abstract: This article presents the methods of zero moment point (ZMP) trajectory evaluation for human locomotion by processing biomechanical data recorded with Kinect-based motion capture (MoCap) system. Our MoCap system consists of four Kinect 2 sensors, using commercial iPi soft markerless tracking and visualization technology. We apply iPi Mocap Studio software to multi-depth sensor video recordings, acquiring visual and biomechanical human gait data, including linear and angular coordinates, velocities, accelerations and center of mass (CoM) position of each joint. Finally, we compute ZMP and ground projection of the CoM (GCOM) trajectories from human body dynamics in MATLAB by two methods, where human body is treated as (1) a single mass point, and (2) multiple mass points (with following ZMP calculation via inertia tensor). The further objective of our research is to reproduce the human-like gait with Russian biped robot AR-601M.

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Paper citation in several formats:
Danilov, I.; Gabbasov, B.; Afanasyev, I. and Magid, E. (2016). ZMP Trajectory from Human Body Locomotion Dynamics Evaluated by Kinect-based Motion Capture System.In Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2016) ISBN 978-989-758-175-5, pages 160-166. DOI: 10.5220/0005726001600166

@conference{visapp16,
author={Igor Danilov. and Bulat Gabbasov. and Ilya Afanasyev. and Evgeni Magid.},
title={ZMP Trajectory from Human Body Locomotion Dynamics Evaluated by Kinect-based Motion Capture System},
booktitle={Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2016)},
year={2016},
pages={160-166},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005726001600166},
isbn={978-989-758-175-5},
}

TY - CONF

JO - Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2016)
TI - ZMP Trajectory from Human Body Locomotion Dynamics Evaluated by Kinect-based Motion Capture System
SN - 978-989-758-175-5
AU - Danilov, I.
AU - Gabbasov, B.
AU - Afanasyev, I.
AU - Magid, E.
PY - 2016
SP - 160
EP - 166
DO - 10.5220/0005726001600166

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