Automated photogrammetric network design using genetic algorithms

This work describes the use of genetic algorithms for automating the photogrammetric network design process. When planning a photogrammetric network, the cameras should be placed in order to satisfy a set of interrelated and competing constraints. Furthermore, when the object is three-dimensional, a combinatorial problem occurs. Genetic algorithms are stochastic optimization techniques, which have proved useful for solving computationally difficult problems with high combinatorial aspects. A system based on genetic algorithms, EPOCA (Evolving POsitions of CAmeras), was implemented using a three-dimensional CAD interface. The system provides the attitude of each camera in the network, taking into account the imaging geometry, as well as several major constraints such as visibility, convergence angle, and workspace constraint. EPOCA reproduces configurations reported in the photogrammetric literature. Moreover, the system can design networks for several adjoining planes and complex objects, opening interesting new research avenues.