Since humans usually prefer to communicate in qualitative and not in quantitative categories, qualitative spatial representations are of great importance for user interfaces of systems that involve spatial tasks. Abstraction is the key for the generation of qualitative representations from observed data. This paper deals with the conversion of motion data into qualitative representations, and it presents a new generalization algorithm that abstracts from irrelevant details of a course of motion. In a further step of abstraction, the shape of a course of motion is used for qualitative representation. Our approach is motivated by findings of our own experimental research on the processing and representation of spatio-temporal information in the human visual system.