Abstract
Multi-view triangulation is an essential step in recovering three-dimensional structure from a set of images. It is a well-studied problem in computer vision with many suboptimal and optimal methods based on different optimality criteria. In this paper, we assess the ability of evolutionary computation (EC) methods in finding highly accurate solutions to this problem. We use an overlaying Luus–Jaakola optimizer to find good parameter configurations and determine appropriate computational budget for the EC methods. Empirical results on synthetic and real data demonstrate the superior performance of EC methods over existing triangulation methods.
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