Digital close-range photogrammetry has been continually growing in presence and extent of use for many years. More recently, as techniques have been developed and refined, it has become heavily involved in recording and documenting cultural heritage objects. As greater accuracy is continually strived for, planning for these projects becomes more and more important.
The purpose of this thesis is to investigate network design in close-range photogrammetry. Six different networks are designed, focusing on different elements such as the distance from the target area, the convergence angle of the network, height of camera stations, and accessibility constraints. Other variables explored include the number of photos taken from each camera station, and the types of coded targets used for the processing.
The recorded images for each network are processed using iWitnessPRO photogrammetry software, by which the coded targets are automatically found and referenced. Results for the various networks are explored, and object point accuracies are further improved through the manual elimination of incorrectly referenced points. The processing yielded results which strongly suggested an increase in network strength based on a large convergence angle and minimal distance from the target area, so long as the entire target area is within the photo.
The results obtained indicate that network design is an important element of close-range photogrammetry projects and should be approached carefully and meaningfully, as it has a very strong bearing on the potential accuracy that will be obtained.