| Summary: | The 3D reconstruction of a scene from 2D images is an important topic in the eld of
Computer Vision due to the high demand in various applications such as gaming, animations,
face recognition, parts inspections, etc. The accuracy of a 3D reconstruction is highly dependent
on the accuracy of the correspondence matching between the images. For the purpose of high
accuracy of 3D reconstruction system using just two images of the scene, it is important to nd
accurate correspondence between the image pairs.
In this thesis, we implement an accurate 3D reconstruction system from two images of
the scene at dierent orientation using a normal digital camera. We use epipolar geometry to
improvise the performance of the initial coarse correspondence matches between the images.
Finally we calculate the reprojection error of the 3D reconstruction system before and after
rening the correspondence matches using the epipolar geometry and compare the performance
between them.
Even though many feature-based correspondence matching techniques provide robust matching
required for 3D reconstruction, it gives only coarse correspondence matching between the
images. This is not sucient to reconstruct the detailed 3D structure of the objects. Therefore
we use our improvised image matching to calculate the camera parameters and implement dense
image matching using thin-plate spline interpolation, which interpolates the surface based on the
initial control points obtained from coarse correspondence matches. Since the thin-plate spline
interpolates highly dense points from a very few control points, the correspondence mapping
between the images are not accurate. We propose a new method to improve the performance of
the dense image matching using epipolar geometry and intensity based thin-plate spline interpolation.
We apply the proposed method for 3D reconstruction using two images. Finally, we
develop systematic evaluation for our dense 3D reconstruction system and discuss the results.
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