Multiple marker tracking in a single-camera system for gait analysis

Cheng Yang, Ukadike Ugbolue, Bruce Carse, Vladimir Stankovic, Lina Stankovic, Philip Rowe

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

Abstract

Human gait analysis for stroke rehabilitation therapy using video processing tools has become popular in recent years. This paper proposes a single-camera system for capturing gait patterns using a Kalman-Structural-Similarity-based algorithm which tracks multiple markers simultaneously. This algorithm is initialized by obtaining the user-selected blocks in the first frame of each video, and the tracker is implemented by using Structural-Similarity image quality assessment algorithm to detect each marker frame by frame within a search area determined by a discrete Kalman filter. Experimental results show the trajectories of the markers fixed on the joints of a human body. The obtained numerical results are used to generate gait information (e.g., knee joint angle) that is later used for diagnostics. The proposed method aims to explore an alternative and portable way to implement human gait analysis with significantly less cost compared to a state-of-the-art 3D motion capture system.
Original languageEnglish
Title of host publication2013 IEEE International Conference on Image Processing
PublisherIEEE
Pages3128-3131
Number of pages4
ISBN (Print)9781479923410
DOIs
Publication statusPublished - 2013
Externally publishedYes

Publication series

NameIEEE International Conference on Image Processing ICIP
PublisherIEEE
ISSN (Print)1522-4880

Keywords

  • Marker tracking
  • Structural-Similarity
  • Gait analysis

Cite this

Yang, C., Ugbolue, U., Carse, B., Stankovic, V., Stankovic, L., & Rowe, P. (2013). Multiple marker tracking in a single-camera system for gait analysis. In 2013 IEEE International Conference on Image Processing (pp. 3128-3131). (IEEE International Conference on Image Processing ICIP). IEEE. https://doi.org/10.1109/ICIP.2013.6738644
Yang, Cheng ; Ugbolue, Ukadike ; Carse, Bruce ; Stankovic, Vladimir ; Stankovic, Lina ; Rowe, Philip. / Multiple marker tracking in a single-camera system for gait analysis. 2013 IEEE International Conference on Image Processing. IEEE, 2013. pp. 3128-3131 (IEEE International Conference on Image Processing ICIP).
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title = "Multiple marker tracking in a single-camera system for gait analysis",
abstract = "Human gait analysis for stroke rehabilitation therapy using video processing tools has become popular in recent years. This paper proposes a single-camera system for capturing gait patterns using a Kalman-Structural-Similarity-based algorithm which tracks multiple markers simultaneously. This algorithm is initialized by obtaining the user-selected blocks in the first frame of each video, and the tracker is implemented by using Structural-Similarity image quality assessment algorithm to detect each marker frame by frame within a search area determined by a discrete Kalman filter. Experimental results show the trajectories of the markers fixed on the joints of a human body. The obtained numerical results are used to generate gait information (e.g., knee joint angle) that is later used for diagnostics. The proposed method aims to explore an alternative and portable way to implement human gait analysis with significantly less cost compared to a state-of-the-art 3D motion capture system.",
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author = "Cheng Yang and Ukadike Ugbolue and Bruce Carse and Vladimir Stankovic and Lina Stankovic and Philip Rowe",
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Yang, C, Ugbolue, U, Carse, B, Stankovic, V, Stankovic, L & Rowe, P 2013, Multiple marker tracking in a single-camera system for gait analysis. in 2013 IEEE International Conference on Image Processing. IEEE International Conference on Image Processing ICIP, IEEE, pp. 3128-3131. https://doi.org/10.1109/ICIP.2013.6738644

Multiple marker tracking in a single-camera system for gait analysis. / Yang, Cheng; Ugbolue, Ukadike; Carse, Bruce; Stankovic, Vladimir; Stankovic, Lina; Rowe, Philip.

2013 IEEE International Conference on Image Processing. IEEE, 2013. p. 3128-3131 (IEEE International Conference on Image Processing ICIP).

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

TY - GEN

T1 - Multiple marker tracking in a single-camera system for gait analysis

AU - Yang, Cheng

AU - Ugbolue, Ukadike

AU - Carse, Bruce

AU - Stankovic, Vladimir

AU - Stankovic, Lina

AU - Rowe, Philip

PY - 2013

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N2 - Human gait analysis for stroke rehabilitation therapy using video processing tools has become popular in recent years. This paper proposes a single-camera system for capturing gait patterns using a Kalman-Structural-Similarity-based algorithm which tracks multiple markers simultaneously. This algorithm is initialized by obtaining the user-selected blocks in the first frame of each video, and the tracker is implemented by using Structural-Similarity image quality assessment algorithm to detect each marker frame by frame within a search area determined by a discrete Kalman filter. Experimental results show the trajectories of the markers fixed on the joints of a human body. The obtained numerical results are used to generate gait information (e.g., knee joint angle) that is later used for diagnostics. The proposed method aims to explore an alternative and portable way to implement human gait analysis with significantly less cost compared to a state-of-the-art 3D motion capture system.

AB - Human gait analysis for stroke rehabilitation therapy using video processing tools has become popular in recent years. This paper proposes a single-camera system for capturing gait patterns using a Kalman-Structural-Similarity-based algorithm which tracks multiple markers simultaneously. This algorithm is initialized by obtaining the user-selected blocks in the first frame of each video, and the tracker is implemented by using Structural-Similarity image quality assessment algorithm to detect each marker frame by frame within a search area determined by a discrete Kalman filter. Experimental results show the trajectories of the markers fixed on the joints of a human body. The obtained numerical results are used to generate gait information (e.g., knee joint angle) that is later used for diagnostics. The proposed method aims to explore an alternative and portable way to implement human gait analysis with significantly less cost compared to a state-of-the-art 3D motion capture system.

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Yang C, Ugbolue U, Carse B, Stankovic V, Stankovic L, Rowe P. Multiple marker tracking in a single-camera system for gait analysis. In 2013 IEEE International Conference on Image Processing. IEEE. 2013. p. 3128-3131. (IEEE International Conference on Image Processing ICIP). https://doi.org/10.1109/ICIP.2013.6738644