In this paper we describe a method for analysing video sequences and for representing them as mosaics or panoramas. Previous work on video mosaicking essentially concentrated on static scenes. We generalise these approaches to the case of a rotating camera observing both static and moving objects where the static portions of the scene are not necessarily dominant, as it has been often hypothesised in the past. We start by describing a robust technique for accurately aligning a large number of video frames under unknown camera rotations and camera settings. The alignment technique combines a feature-based method (initialisation and refinement) with rough motion segmentation followed by a colour-based direct method (final adjustment). This precise frame-to-frame alignment allows the dynamic building of a background representation as well as an efficient segmentation of each image such that moving regions of arbitrary shape and size are aligned with the static background. Thus a motion panorama visualises both dynamic and static scene elements in a geometrically consistent way. Extensive experiments applied to archived videos of track-and-field events validate the approach.