Separate adjustment in close-range photogrammetry
Industrial manufacturing processes will increasingly require high-speed 3D measurement. If a photogrammetric measurement system is used, cameras will typically be pre-calibrated for interior orientation parameters. The conventional bundle adjustment may be computationally too expensive and other algorithms such as DLT or direct intersection can be used. However, these methods do not provide optimum solutions. In this paper, the separate adjustment method is introduced. This method is based on the separate least squares estimation (LSE) of both the camera exterior orientation parameters and the 3D co-ordinates of the object points. The same results as the bundle adjustment are produced but with a significantly lower computational load. This method is analogous to iterative solution algorithms such as Jacobi or GaussSeidel; however, the implementation is different. It is also similar to the successive application of resection and intersection under certain circumstances. The separate adjustment algorithm is described and compared with the bundle adjustment in terms of results, speed and memory requirements.
separate adjustment bundle adjustment least squares real time sensor orientation 3d object point co-ordinate estimation