PCA based 3D shape reconstruction of human foot using multiple viewpoint cameras

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Abstract

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. © 2008 Springer-Verlag Berlin Heidelberg.

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Amstutz, E., Teshima, T., Kimura, M., Mochimaru, M., & Saito, H. (2008). PCA based 3D shape reconstruction of human foot using multiple viewpoint cameras. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5008 LNCS, pp. 161–170). https://doi.org/10.1007/978-3-540-79547-6_16

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