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 contributionpeer-review


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
Number of pages4
ISBN (Print)9781479923410
Publication statusPublished - 2013
Externally publishedYes

Publication series

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


  • Marker tracking
  • Structural-Similarity
  • Gait analysis


Dive into the research topics of 'Multiple marker tracking in a single-camera system for gait analysis'. Together they form a unique fingerprint.

Cite this