Abstract
This paper addresses the 3D reconstruction of non-rigid surfaces deforming isometrically. In fact, this reconstruction process aims at the estimation of isometric 3D surface. To this end, a ToF camera is used with a conventional monocular camera. The goal is to use the high-resolution images from the RGB camera in combination with the low-resolution depth map to enhance the estimation of non-rigid shapes. We describe how to model an isometric surface by means of a triangular mesh. The ToF sensor provides the depth of feature points, which is subsequently used to obtain the depth of the mesh vertices by means of linear programming-based approach. Given the mesh depth data, a second-order cone programming method is then developed to determine the image points of the mesh vertices. Bundle adjustment is then used to isometrically reconstruct the surfaces. Experimental results show that the proposed approach is robust against noise, generating accurate 3D reconstructions despite the low-resolution of the depth images.
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Hosseini, S.J., Araujo, H. (2014). 3D Estimation of Isometric Surfaces Using a ToF-Based Approach. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2014. Lecture Notes in Computer Science, vol 8888. Springer, Cham. https://doi.org/10.1007/978-3-319-14364-4_13
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DOI: https://doi.org/10.1007/978-3-319-14364-4_13
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-14363-7
Online ISBN: 978-3-319-14364-4
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