DocumentCode
3029766
Title
A gait analysis system using two cameras with orthogonal view
Author
Li, Yu-Ren ; Miaou, Shaou-Gang ; Hung, Charles Kater ; Sese, Julius Tube
Author_Institution
Dept. of Electron. Eng., Chung Yuan Christian Univ., Chungli, Taiwan
fYear
2011
fDate
26-28 July 2011
Firstpage
2841
Lastpage
2844
Abstract
Tradition gait analysis systems capture the image of a walking subject from either front view or side view. Since the walking direction allowed by the systems is highly restricted, they are inconvenient for long-term evaluation in casual environments (such as home). This study proposes a human gait analysis system with much less restriction on walking direction. In the system, we use the images obtained from multi-viewing angles and performs human gait analysis based on a set of chosen features, including the center of gravity (COG) and pace length, obtained from human silhouette images. The system successfully extracts gait features from various walking directions and integrates the features obtained from two cameras having orthogonal views. The integration principle is discussed in details. The integrated feature is then compared with the ideal gait feature obtained from the camera whose viewing direction is perpendicular to the walking path, resulting in very high correlation. This study shows that a vision-based gait analyzer with two orthogonally arranged cameras has the potential to remove the walking direction restriction.
Keywords
cameras; computer vision; feature extraction; gait analysis; image motion analysis; cameras; center of gravity; gait feature extraction; human gait analysis system; human silhouette images; orthogonal view; pace length; vision-based gait analyzer; walking direction; Cameras; Correlation; Feature extraction; Hidden Markov models; Humans; Image recognition; Legged locomotion; Gait Analysis; Orthogonal Views; Silhouette Image; Two Cameras;
fLanguage
English
Publisher
ieee
Conference_Titel
Multimedia Technology (ICMT), 2011 International Conference on
Conference_Location
Hangzhou
Print_ISBN
978-1-61284-771-9
Type
conf
DOI
10.1109/ICMT.2011.6002046
Filename
6002046
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