A Visual-Inertial Approach to Human Gait Estimation

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper addresses the problem of gait estimation using visual and inertial data, as well as human motion models. Specifically, a batch least-squares (BLS) algorithm is presented that fuses data from a minimal set of sensors [two inertial measurement units (IMUs), one on each foot, and a head-mounted IMU-camera pair] along with motion constraints corresponding to the different walking states, to estimate the person's head and feet poses. Subsequently, gait models are employed to solve for the lower-body's posture and generate its animation. Experimental results against the VICON motion capture system demonstrate the accuracy of the proposed minimal sensors-based system for determining a person's motion.

Original languageEnglish (US)
Title of host publication2018 IEEE International Conference on Robotics and Automation, ICRA 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages4614-4621
Number of pages8
ISBN (Electronic)9781538630815
DOIs
StatePublished - Sep 10 2018
Event2018 IEEE International Conference on Robotics and Automation, ICRA 2018 - Brisbane, Australia
Duration: May 21 2018May 25 2018

Publication series

NameProceedings - IEEE International Conference on Robotics and Automation
ISSN (Print)1050-4729

Conference

Conference2018 IEEE International Conference on Robotics and Automation, ICRA 2018
CountryAustralia
CityBrisbane
Period5/21/185/25/18

Fingerprint

Units of measurement
Sensors
Electric fuses
Animation
Cameras

Cite this

Ahmed, A., & Roumeliotis, S. (2018). A Visual-Inertial Approach to Human Gait Estimation. In 2018 IEEE International Conference on Robotics and Automation, ICRA 2018 (pp. 4614-4621). [8460871] (Proceedings - IEEE International Conference on Robotics and Automation). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICRA.2018.8460871

A Visual-Inertial Approach to Human Gait Estimation. / Ahmed, Ahmed; Roumeliotis, Stergios.

2018 IEEE International Conference on Robotics and Automation, ICRA 2018. Institute of Electrical and Electronics Engineers Inc., 2018. p. 4614-4621 8460871 (Proceedings - IEEE International Conference on Robotics and Automation).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Ahmed, A & Roumeliotis, S 2018, A Visual-Inertial Approach to Human Gait Estimation. in 2018 IEEE International Conference on Robotics and Automation, ICRA 2018., 8460871, Proceedings - IEEE International Conference on Robotics and Automation, Institute of Electrical and Electronics Engineers Inc., pp. 4614-4621, 2018 IEEE International Conference on Robotics and Automation, ICRA 2018, Brisbane, Australia, 5/21/18. https://doi.org/10.1109/ICRA.2018.8460871
Ahmed A, Roumeliotis S. A Visual-Inertial Approach to Human Gait Estimation. In 2018 IEEE International Conference on Robotics and Automation, ICRA 2018. Institute of Electrical and Electronics Engineers Inc. 2018. p. 4614-4621. 8460871. (Proceedings - IEEE International Conference on Robotics and Automation). https://doi.org/10.1109/ICRA.2018.8460871
Ahmed, Ahmed ; Roumeliotis, Stergios. / A Visual-Inertial Approach to Human Gait Estimation. 2018 IEEE International Conference on Robotics and Automation, ICRA 2018. Institute of Electrical and Electronics Engineers Inc., 2018. pp. 4614-4621 (Proceedings - IEEE International Conference on Robotics and Automation).
@inproceedings{2164074719894b74a2e3499e0f23753e,
title = "A Visual-Inertial Approach to Human Gait Estimation",
abstract = "This paper addresses the problem of gait estimation using visual and inertial data, as well as human motion models. Specifically, a batch least-squares (BLS) algorithm is presented that fuses data from a minimal set of sensors [two inertial measurement units (IMUs), one on each foot, and a head-mounted IMU-camera pair] along with motion constraints corresponding to the different walking states, to estimate the person's head and feet poses. Subsequently, gait models are employed to solve for the lower-body's posture and generate its animation. Experimental results against the VICON motion capture system demonstrate the accuracy of the proposed minimal sensors-based system for determining a person's motion.",
author = "Ahmed Ahmed and Stergios Roumeliotis",
year = "2018",
month = "9",
day = "10",
doi = "10.1109/ICRA.2018.8460871",
language = "English (US)",
series = "Proceedings - IEEE International Conference on Robotics and Automation",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "4614--4621",
booktitle = "2018 IEEE International Conference on Robotics and Automation, ICRA 2018",

}

TY - GEN

T1 - A Visual-Inertial Approach to Human Gait Estimation

AU - Ahmed, Ahmed

AU - Roumeliotis, Stergios

PY - 2018/9/10

Y1 - 2018/9/10

N2 - This paper addresses the problem of gait estimation using visual and inertial data, as well as human motion models. Specifically, a batch least-squares (BLS) algorithm is presented that fuses data from a minimal set of sensors [two inertial measurement units (IMUs), one on each foot, and a head-mounted IMU-camera pair] along with motion constraints corresponding to the different walking states, to estimate the person's head and feet poses. Subsequently, gait models are employed to solve for the lower-body's posture and generate its animation. Experimental results against the VICON motion capture system demonstrate the accuracy of the proposed minimal sensors-based system for determining a person's motion.

AB - This paper addresses the problem of gait estimation using visual and inertial data, as well as human motion models. Specifically, a batch least-squares (BLS) algorithm is presented that fuses data from a minimal set of sensors [two inertial measurement units (IMUs), one on each foot, and a head-mounted IMU-camera pair] along with motion constraints corresponding to the different walking states, to estimate the person's head and feet poses. Subsequently, gait models are employed to solve for the lower-body's posture and generate its animation. Experimental results against the VICON motion capture system demonstrate the accuracy of the proposed minimal sensors-based system for determining a person's motion.

UR - http://www.scopus.com/inward/record.url?scp=85063144125&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85063144125&partnerID=8YFLogxK

U2 - 10.1109/ICRA.2018.8460871

DO - 10.1109/ICRA.2018.8460871

M3 - Conference contribution

T3 - Proceedings - IEEE International Conference on Robotics and Automation

SP - 4614

EP - 4621

BT - 2018 IEEE International Conference on Robotics and Automation, ICRA 2018

PB - Institute of Electrical and Electronics Engineers Inc.

ER -