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Title: Thin Lens-Based Geometric Surface Inversion for Multiview Stereo
Committee:
Dr. Yezzi, Advisor
Dr. Dellaert, Chair
Dr. Vela
Abstract:
The objective of the proposed research is to develop a fully generative algorithm for the reconstruction of dense three-dimensional shapes from scene measurements under varying viewpoints and levels of focus. This will be done by modifying existing methods using a thin lens optical model in place of the currently used pinhole model. While easily stated, this requires a significant mathematical reformulation from the bottom up as the simple perspective projection assumed by the pinhole model and utilized by current methods no longer applies under the more general thin lens model. New expressions for the forward modeling of image formation as well as model inversion will be developed. For the former, image irradiance will be related to scene radiance using energy conservation, and for the latter, the sensitivities of image irradiance to perturbations in both the scene radiance and geometry will be analyzed. From this, numerical implementations of the forward and inverse models will be developed and programmed, allowing for experimental verification of the algorithm in both the piecewise constant and piecewise smooth radiance cases. The jump in model complexity will allow for better reconstruction when the available images are not well-focused, and it should provide a unified framework where different image cues are treated equally.
