Active shape models—their training and application
Computer Vision and Image Understanding
Multiple view geometry in computer vision
Multiple view geometry in computer vision
Boundary Finding with Correspondence Using Statistical Shape Models
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
A Passive Full Body Scanner Using Shape from Silhouettes
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 1
Human Foot Reconstruction from Multiple Camera Images with Foot Shape Database
IEICE - Transactions on Information and Systems
The caesar project: a 3-D surface anthropometry survey
3DIM'99 Proceedings of the 2nd international conference on 3-D digital imaging and modeling
Preliminary study on dynamic foot model
ICDHM'11 Proceedings of the Third international conference on Digital human modeling
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This article describes a multiple camera based method to reconstruct a 3D shape of a human foot. From a feet database, an initial 3D model of the foot represented by a cloud of points is built. In addition, some shape parameters, which characterize any foot at more than 92%, are defined by using Principal Component Analysis. Then, the 3D model is adapted to the foot of interest captured in multiple images based on "active shape models" methods by applying some constraints (edge points' distance, color variance for example). We insist here on the experiment part where we demonstrate the efficiency of the proposed method on a plastic foot model, and on real human feet with various shapes. We compare different ways to texture the foot, and conclude that using projectors can improve drastically the reconstruction's accuracy. Based on experimental results, we finally propose some improvements regarding to the system integration.