This paper presents labelled-object velocimetry (LOV) - a technique to determine the velocities of labelled objects in multiphase flow. LOV is based on spatial correlations similar to those used in particle-image velocimetry (PIV) but employs grey-level shadowgraph images to determine object velocities. Object detection and labelling are performed using a classical image-processing algorithm. In contrast to PIV, interrogation areas in LOV are not uniformly distributed. Instead, these areas surround objects, and therefore, depend on object positions and sizes. Additionally, the proposed technique recalls a previously developed algorithm (Laupsien et al., 2019) to distinguish between single bubbles and complex situations, such as overlays, breakups and coalescences. This algorithm-based object selection (ABOS) provides a statistically reliable sample of the entire bubble swarm in terms of size and shape. Although both techniques are completely independent, they can be combined to link object velocities to their geometrical characteristics. Thus, the LOV technique can be used to ascertain velocity-object diameter histograms.