A Method for Registration of 3-D Shapes
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special issue on interpretation of 3-D scenes—part II
Object modelling by registration of multiple range images
Image and Vision Computing - Special issue: range image understanding
Surface Modeling for CAD - Cam
Surface Modeling for CAD - Cam
Convergence Properties of the Nelder--Mead Simplex Method in Low Dimensions
SIAM Journal on Optimization
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In this paper, a practical methodology of surface-based registration supported by an automated laser surface scanning system to achieve good mapping performance is reported. The laser scanning system is used to digitize the facial feature of a phantom so as to mesh the physical space into triangular frame. The image space is established by translating the corresponding CT image into point set through using the medical image software tools. The image-to-physical registration task is carried out by a direct searching mechanism together with the objective function in an optimal fashion. The unconstrained nonlinear optimization algorithm performs the optimal searching iteration to find those parameters in the rigid-body transformation until the sum of the squared normal distances is minimized. Considering mapping the massive points in registration task would consume the computation time, there is only a suitable sample size to stand for the entire population with sufficient confidence and accuracy are extracted statistically from the CT point space to map to the laser scanning space. Registration results evaluated by gauging the position errors of the landmarks on phantom forehead show the proposed methodology has good ability to perform the image-to-physical registration.