Improved Trajectory Reconstruction for Markerless Pose Estimation

R. James Cotton; Anthony Cimorelli; Kunal Shah; Shawana Anarwala; Scott Uhlrich; Tasos Karakostas

doi:10.1109/EMBC40787.2023.10340745

Improved Trajectory Reconstruction for Markerless Pose Estimation

R. James Cotton^*, Anthony Cimorelli, Kunal Shah, Shawana Anarwala, Scott Uhlrich, Tasos Karakostas

^*Corresponding author for this work

Physical Medicine and Rehabilitation

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Scopus citations

Abstract

Markerless pose estimation allows reconstructing human movement from multiple synchronized and calibrated views, and has the potential to make movement analysis easy and quick, including gait analysis. This could enable much more frequent and quantitative characterization of gait impairments, allowing better monitoring of outcomes and responses to interventions. However, the impact of different keypoint detectors and reconstruction algorithms on markerless pose estimation accuracy has not been thoroughly evaluated. We tested these algorithmic choices on data acquired from a multicamera system from a heterogeneous sample of 53 individuals in a rehabilitation hospital. We found that using a top-down keypoint detector and reconstructing trajectories with an implicit function enabled accurate, smooth, and anatomically plausible trajectories, with a noise in the step width estimates compared to a GaitRite walkway of only 9mm.

Original language	English (US)
Title of host publication	2023 45th Annual International Conference of the IEEE Engineering in Medicine and Biology Conference, EMBC 2023 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9798350324471
DOIs	https://doi.org/10.1109/EMBC40787.2023.10340745
State	Published - 2023
Event	45th Annual International Conference of the IEEE Engineering in Medicine and Biology Conference, EMBC 2023 - Sydney, Australia Duration: Jul 24 2023 → Jul 27 2023

Publication series

Name	Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
ISSN (Print)	1557-170X

Conference

Conference	45th Annual International Conference of the IEEE Engineering in Medicine and Biology Conference, EMBC 2023
Country/Territory	Australia
City	Sydney
Period	7/24/23 → 7/27/23

Funding

This work was generously supported by the Research Accelerator Program of the Shirley Ryan AbilityLab and with funding from the Restore Center P2C (NIH P2CHD101913). *[email protected], 1. Shirley Ryan AbilityLab, 2. Department of Physical Medicine and Rehabilitation, Northwestern University, 3. Stanford University

ASJC Scopus subject areas

Signal Processing
Health Informatics
Computer Vision and Pattern Recognition
Biomedical Engineering

Access to Document

10.1109/EMBC40787.2023.10340745

Cite this

Cotton, R. J., Cimorelli, A., Shah, K., Anarwala, S., Uhlrich, S., & Karakostas, T. (2023). Improved Trajectory Reconstruction for Markerless Pose Estimation. In 2023 45th Annual International Conference of the IEEE Engineering in Medicine and Biology Conference, EMBC 2023 - Proceedings (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/EMBC40787.2023.10340745

Cotton, R. James ; Cimorelli, Anthony ; Shah, Kunal et al. / Improved Trajectory Reconstruction for Markerless Pose Estimation. 2023 45th Annual International Conference of the IEEE Engineering in Medicine and Biology Conference, EMBC 2023 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2023. (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS).

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abstract = "Markerless pose estimation allows reconstructing human movement from multiple synchronized and calibrated views, and has the potential to make movement analysis easy and quick, including gait analysis. This could enable much more frequent and quantitative characterization of gait impairments, allowing better monitoring of outcomes and responses to interventions. However, the impact of different keypoint detectors and reconstruction algorithms on markerless pose estimation accuracy has not been thoroughly evaluated. We tested these algorithmic choices on data acquired from a multicamera system from a heterogeneous sample of 53 individuals in a rehabilitation hospital. We found that using a top-down keypoint detector and reconstructing trajectories with an implicit function enabled accurate, smooth, and anatomically plausible trajectories, with a noise in the step width estimates compared to a GaitRite walkway of only 9mm.",

author = "Cotton, {R. James} and Anthony Cimorelli and Kunal Shah and Shawana Anarwala and Scott Uhlrich and Tasos Karakostas",

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Cotton, RJ, Cimorelli, A, Shah, K, Anarwala, S, Uhlrich, S & Karakostas, T 2023, Improved Trajectory Reconstruction for Markerless Pose Estimation. in 2023 45th Annual International Conference of the IEEE Engineering in Medicine and Biology Conference, EMBC 2023 - Proceedings. Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, Institute of Electrical and Electronics Engineers Inc., 45th Annual International Conference of the IEEE Engineering in Medicine and Biology Conference, EMBC 2023, Sydney, Australia, 7/24/23. https://doi.org/10.1109/EMBC40787.2023.10340745

Improved Trajectory Reconstruction for Markerless Pose Estimation. / Cotton, R. James; Cimorelli, Anthony; Shah, Kunal et al.
2023 45th Annual International Conference of the IEEE Engineering in Medicine and Biology Conference, EMBC 2023 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2023. (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AU - Karakostas, Tasos

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AB - Markerless pose estimation allows reconstructing human movement from multiple synchronized and calibrated views, and has the potential to make movement analysis easy and quick, including gait analysis. This could enable much more frequent and quantitative characterization of gait impairments, allowing better monitoring of outcomes and responses to interventions. However, the impact of different keypoint detectors and reconstruction algorithms on markerless pose estimation accuracy has not been thoroughly evaluated. We tested these algorithmic choices on data acquired from a multicamera system from a heterogeneous sample of 53 individuals in a rehabilitation hospital. We found that using a top-down keypoint detector and reconstructing trajectories with an implicit function enabled accurate, smooth, and anatomically plausible trajectories, with a noise in the step width estimates compared to a GaitRite walkway of only 9mm.

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Cotton RJ, Cimorelli A, Shah K, Anarwala S, Uhlrich S, Karakostas T. Improved Trajectory Reconstruction for Markerless Pose Estimation. In 2023 45th Annual International Conference of the IEEE Engineering in Medicine and Biology Conference, EMBC 2023 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2023. (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS). doi: 10.1109/EMBC40787.2023.10340745

Improved Trajectory Reconstruction for Markerless Pose Estimation

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