Abstract
This chapter starts with a review of sensor planning and the problem of photogrammetric network design. Next, a quick review of multiobjective problem design is offered in order to prepare for the analysis of sensor planning from a multiobjective standpoint. Thus, three main criteria – accurate 3D reconstruction, efficient robot motion, and computational cost – relevant to the task are introduced towards the achievement of Pareto optimal sensing strategies. As a result, an evolutionary-based optimization methodology is outlined with the goal of planning photogrammetric networks. Experimental results in simulation and practice are provided, giving novel and well-known camera configurations that validate the practicality of the proposed methodology.
“Everyone by now presumably knows about the danger of premature optimization. I think we should be just as worried about premature design – designing too early what a program should do.”
– Paul Graham
“The question is not what you look at, but what you see.”
– Henry David Thoreau
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© 2016 Springer-Verlag Berlin Heidelberg
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Olague, G. (2016). Multiobjective Sensor Planning for Accurate Reconstruction. In: Evolutionary Computer Vision. Natural Computing Series. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-43693-6_7
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DOI: https://doi.org/10.1007/978-3-662-43693-6_7
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Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-662-43692-9
Online ISBN: 978-3-662-43693-6
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