3D shape from silhouette points in registered 2D images using conjugate gradient method

Andrzej Szymczak; William Hoff; Mohamed Mahfouz

doi:10.1117/12.843885

12 March 2010 3D shape from silhouette points in registered 2D images using conjugate gradient method

Andrzej Szymczak, William Hoff, Mohamed Mahfouz

Proceedings Volume 7623, Medical Imaging 2010: Image Processing; 762316 (2010) https://doi.org/10.1117/12.843885
Event: SPIE Medical Imaging, 2010, San Diego, California, United States

Abstract

We describe a simple and robust algorithm for estimating 3D shape given a number of silhouette points obtained from two or more viewpoints and a parametric model of the shape. Our algorithm minimizes (in the least squares sense) the distances from the lines obtained by unprojecting the silhouette points to 3D to their closest silhouette points on the 3D shape. The solution is found using an iterative approach. In each iteration, we locally approximate the least squares problem with a degree-4 polynomial function. The approximate problem is solved using a nonlinear conjugate gradient solver that takes advantage of its structure to perform exact and global line searches. We tested our algorithm by applying it to reconstruct patient-specific femur shapes from simulated biplanar X-ray images.

Citation Download Citation

Andrzej Szymczak, William Hoff, and Mohamed Mahfouz "3D shape from silhouette points in registered 2D images using conjugate gradient method", Proc. SPIE 7623, Medical Imaging 2010: Image Processing, 762316 (12 March 2010); https://doi.org/10.1117/12.843885

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