Abstract
Gait, or the style of walking, has been recently a popular topic in vision-based analysis. Most vision-based works about gait are devoted to the application of human recognition, but abnormal walking styles are rarely discussed. Accordingly, a vision-based method is proposed to analyze abnormal types of walking. In the proposed method, a background subtraction algorithm is applied to segment out the silhouette of the walker at each frame in a sequence. For each frame, we define a feature based on the length between two legs and the height of the individual, called aspect ratio (AR). By observing this feature value across time (or frame), a periodic wave is obtained. With this analysis, a few abnormal types of walking can be distinguished. Since an oblique camera view angle causes a distortion of the AR wave, a rectification mechanism is proposed based on a camera pinhole model to reduce the view angle effect. The experimental results show that the proposed rectification method identified abnormal walking patterns reliably irrespective of the direction in which the individual walks relative to the camera plane.
| Original language | English |
|---|---|
| Title of host publication | Advances in Intelligent Systems and Applications - Volume 2 |
| Subtitle of host publication | Proceedings of the International Computer |
| Editors | Chang Ruay-Shiung, Peng Sheng-Lung, Lin Chia-Chen |
| Pages | 521-529 |
| Number of pages | 9 |
| DOIs | |
| Publication status | Published - 2013 Jun 28 |
Publication series
| Name | Smart Innovation, Systems and Technologies |
|---|---|
| Volume | 21 |
| ISSN (Print) | 2190-3018 |
| ISSN (Electronic) | 2190-3026 |
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All Science Journal Classification (ASJC) codes
- Decision Sciences(all)
- Computer Science(all)
Cite this
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A New View-Calibrated Approach for Abnormal Gait Detection. / Lin, Kuo Wei; Wang, Shu Ting; Chung, Pau-Choo; Yang, Ching Fang.
Advances in Intelligent Systems and Applications - Volume 2: Proceedings of the International Computer. ed. / Chang Ruay-Shiung; Peng Sheng-Lung; Lin Chia-Chen. 2013. p. 521-529 (Smart Innovation, Systems and Technologies; Vol. 21).Research output: Chapter in Book/Report/Conference proceeding › Chapter
TY - CHAP
T1 - A New View-Calibrated Approach for Abnormal Gait Detection
AU - Lin, Kuo Wei
AU - Wang, Shu Ting
AU - Chung, Pau-Choo
AU - Yang, Ching Fang
PY - 2013/6/28
Y1 - 2013/6/28
N2 - Gait, or the style of walking, has been recently a popular topic in vision-based analysis. Most vision-based works about gait are devoted to the application of human recognition, but abnormal walking styles are rarely discussed. Accordingly, a vision-based method is proposed to analyze abnormal types of walking. In the proposed method, a background subtraction algorithm is applied to segment out the silhouette of the walker at each frame in a sequence. For each frame, we define a feature based on the length between two legs and the height of the individual, called aspect ratio (AR). By observing this feature value across time (or frame), a periodic wave is obtained. With this analysis, a few abnormal types of walking can be distinguished. Since an oblique camera view angle causes a distortion of the AR wave, a rectification mechanism is proposed based on a camera pinhole model to reduce the view angle effect. The experimental results show that the proposed rectification method identified abnormal walking patterns reliably irrespective of the direction in which the individual walks relative to the camera plane.
AB - Gait, or the style of walking, has been recently a popular topic in vision-based analysis. Most vision-based works about gait are devoted to the application of human recognition, but abnormal walking styles are rarely discussed. Accordingly, a vision-based method is proposed to analyze abnormal types of walking. In the proposed method, a background subtraction algorithm is applied to segment out the silhouette of the walker at each frame in a sequence. For each frame, we define a feature based on the length between two legs and the height of the individual, called aspect ratio (AR). By observing this feature value across time (or frame), a periodic wave is obtained. With this analysis, a few abnormal types of walking can be distinguished. Since an oblique camera view angle causes a distortion of the AR wave, a rectification mechanism is proposed based on a camera pinhole model to reduce the view angle effect. The experimental results show that the proposed rectification method identified abnormal walking patterns reliably irrespective of the direction in which the individual walks relative to the camera plane.
UR - http://www.scopus.com/inward/record.url?scp=84879313676&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84879313676&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-35473-1_52
DO - 10.1007/978-3-642-35473-1_52
M3 - Chapter
AN - SCOPUS:84879313676
SN - 9783642354724
T3 - Smart Innovation, Systems and Technologies
SP - 521
EP - 529
BT - Advances in Intelligent Systems and Applications - Volume 2
A2 - Ruay-Shiung, Chang
A2 - Sheng-Lung, Peng
A2 - Chia-Chen, Lin
ER -