HIDDEN VARIABLE RESULTANT APPROACH FOR CLASSICAL COMPUTER VISION PROBLEMS
Many problems in computer vision may be formulated as minimal problems; problems that require a minimal number of inputs and solving them equals to solve a system of non-linear polynomial equations with a finite number of solutions. Problems like relative and absolute camera pose computation fall into this category. This systems of polynomials usually do not have a straightforward solution, which makes the general algorithms for solving systems of polynomials not performant enough. This raises the need to develop concrete algorithms that solve those particular problems. This thesis will ...
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