Name
Title | ||
|---|---|---|
Coarse-to-fine markerless gait analysis based on PCA and Gauss-Laguerre decomposition |
Abstract | ||
|---|---|---|
Human movement analysis is generally performed through the utilization of marker-based systems, which allow reconstructing, with high levels of accuracy, the trajectories of markers allocated on specific points of the human body. Marker based systems, however, show some drawbacks that can be overcome by the use of video systems applying markerless techniques. In this paper, a specifically designed computer vision technique for the detection and tracking of relevant body points is presented. It is based on the Gauss-Laguerre Decomposition, and a Principal Component Analysis Technique (PCA) is used to circumscribe the region of interest. Results obtained on both synthetic and experimental tests provide significant reduction of the computational costs, with no significant reduction of the tracking accuracy. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1117/12.595171 | PROCEEDINGS OF THE SOCIETY OF PHOTO-OPTICAL INSTRUMENTATION ENGINEERS (SPIE) |
Keywords | Field | DocType |
markerless,gait analysis,HMA,PCA,Gauss-Laguerre,motion analysis | Movement analysis,Computer vision,Gauss,Laguerre polynomials,Gait analysis,Artificial intelligence,Motion analysis,Engineering,Region of interest,Principal component analysis | Conference |
Volume | ISSN | Citations |
5747 | 0277-786X | 1 |
PageRank | References | Authors |
0.37 | 7 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| michela goffredo | 1 | 1 | 0.37 |
| Maurizio Schmid | 2 | 89 | 16.32 |
| Silvia Conforto | 3 | 94 | 19.87 |
| Marco Carli | 4 | 158 | 9.71 |
| A Neri | 5 | 679 | 72.31 |
| Tommaso D'Alessio | 6 | 58 | 8.46 |