Object recognition in digital photogrammetry

Object recognition and image understanding have increasingly become major s ubjects of interest for research activity in digital photogrammetry. This p aper provides an overview of object recognition in photogrammetry, beginnin g with a problem statement and brief paradigm description. In order to exem plify the concept, automatic interior orientation is presented as an object recognition problem. Subsequent sections discuss the current status of obj ect recognition by identifying relevant criteria, such as modelling, system strategies and inference components. Such criteria are useful for comparin g object recognition systems or proposed approaches. Strengths and weakness es of current systems are summarized, followed by a more detailed analysis of the modelling problem. Finally, two new approaches (scale-space and fusi on of multisensor/multispectral data) are mentioned. These approaches serve as examples of promising new trends which have the potential of advancing object recognition to a new level.