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The aim of the course is to study computer vision,
which tries to "make computers see and interpret"
using the observations in the form of multiple
2D images or 3D images. Sophisticated computational
techniques are developed with the goal of estimating
and making inferences about the geometric and dynamic
properties of the 3D world around us. A tentative list
of topics for the course includes: review of camera
models/calibration, review of projective geometry,
introductory differantial geometry, 3D object reconstruction
from two (multiple) views, volumetric 3D reconstruction,
2D and 3D motion estimation, image stitching/panorama,
fetaure extraction and matching (sift,...), image inpainting
, image blending/compositing, and other state-of-the-art 3D
vision topics. The course will provide the participants with
an up to date back ground in 3Dimensional computer vision.
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