Abstract | ||
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Accurate measurement of foot shape feature parameters is extremely important in the process of customized shoemaking. A 3D foot's depth image collected by second-generation Kinect is used to propose a foot shape feature parameter measurement algorithm. Through 3D reconstruction of foot based on improved interactive closest points algorithm, the coordinate transformation, feature point selection, and B-spline curve fitting algorithm, the foot length, foot width, metatarsale girth, and other foot feature parameters were calculated. The 3D foot measurement system using this algorithm is tested, and the results of multiple measurements have a mean variance of less than 0.3mm. The average error between the algorithm calculation result and the manual measurement result is less than 0.85mm. The stability and accuracy of the system meet the requirements of custom shoes. It lays a good foundation for the automation and standardization of customized shoemaking. |
Year | DOI | Venue |
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2018 | 10.1186/s13640-018-0368-5 | EURASIP JOURNAL ON IMAGE AND VIDEO PROCESSING |
Keywords | Field | DocType |
Kinect sensor,Foot measurement,Depth image,3D reconstruction,Curve fitting | Coordinate system,Computer vision,Foot width,Pattern recognition,Curve fitting,Computer science,Algorithm,Foot (unit),Automation,Artificial intelligence,Biometrics,3D reconstruction | Journal |
ISSN | Citations | PageRank |
1687-5176 | 0 | 0.34 |
References | Authors | |
13 | 6 |
Name | Order | Citations | PageRank |
---|---|---|---|
Wang Mo | 1 | 1 | 1.05 |
Wang Xin'an | 2 | 0 | 0.34 |
Fan Zhuochen | 3 | 0 | 0.34 |
Zhang Sixu | 4 | 0 | 0.34 |
Chen Peng | 5 | 8 | 5.25 |
Zhong Liu | 6 | 148 | 26.70 |