We present a novel method that determines whether a macula centered retinal image is from the left or right eye and automatically detects the optic disc, the fovea and the vascular arch by inferring the location of a set of landmarks placed on these structures. The algorithm relies on a specific energy function that combines global and local cues. The global cues are derived from vascular atlases of the vessel orientation and thickness on the retina as well as a vascular distance map. A fourth component models the local appearance around each of the landmarks in the model and is able to estimate the distance between a position in the image and the target position of a landmark. For the minimization of the energy function a combination of optimization methods is used. We compare the results of several different system setups and combinations of energy function components with the performance of a second human observer. The best performing system localizes the OD in 91\% of all cases, the fovea in 94\% of all cases and correctly positions 74\% of all vessel landmarks. The results show that a combination of global and local energy function components is required to obtain optimal results.