Optimization without minimization search: Constraint satisfaction by orthogonal projection with applications to multiview triangulation

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Abstract

We present an alternative approach to what we call the "standard optimization", which minimizes a cost function by searching a parameter space. Instead, our approach "projects" in the joint observation space onto the manifold defined by the "consistency constraint", which de-mands that any minimal subset of observations produce the same result. This approach avoids many difficulties encountered in the standard opti-mization. As typical examples, we apply it to line fitting and multiview triangulation. The latter produces a new algorithm far more efficient than existing methods. We also discuss the optimality of our approach. Copyright © 2010 The Institute of Electronics, Information and Communication Engineers.

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Kanatani, K., Sugaya, Y., & Niitsuma, H. (2010). Optimization without minimization search: Constraint satisfaction by orthogonal projection with applications to multiview triangulation. IEICE Transactions on Information and Systems, E93-D(10), 2836–2845. https://doi.org/10.1587/transinf.E93.D.2836

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