Name
Abstract | ||
|---|---|---|
When we are conducting an investigation in gait symmetry analysis, we usually grouped the test objects by decade intervals. However, this artificial division method has a large defect that does not truly reflect the human relationship between age and physical condition. Therefore, we found a new grouping method while clustering on the values of the difference in gait symmetry. The reason for using the affinity propagation clustering algorithm was that it can do clustering on data while passing the original information not the random values to processing clustering. And meanwhile this algorithm has good performance and efficiency. It will help us to do gait analysis more effectively, and also more reasonable to explain the relationship of human gait and age, or gait and other characteristics. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/CIT.2010.295 | CIT |
Keywords | Field | DocType |
pattern clustering,new grouping method,pattern classification,decade interval,data analysis,artificial division method,affinity propagation,affinity propagation clustering,gait analysis,gait symmetry,processing clustering,classification,human gait,gait symmetry analysis,human relationship,clustering,symmetry,clustering algorithms,algorithm design and analysis | Algorithm design,Pattern recognition,Affinity propagation,Gait,Correlation clustering,Computer science,Gait analysis,Artificial intelligence,Gait (human),Cluster analysis,Affinity propagation clustering | Conference |
ISBN | Citations | PageRank |
978-1-4244-7547-6 | 1 | 0.37 |
References | Authors | |
2 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Susu Jiang | 1 | 26 | 5.50 |
| Bofeng Zhang | 2 | 179 | 41.38 |
| Weimin Xu | 3 | 61 | 7.98 |
| Daming Wei | 4 | 215 | 44.97 |