In this paper, we propose an efficient wavelet-based approach to achieve flexible and robust motion trajectory matching of video objects. By using the wavelet transform, our algorithm decomposes the raw object trajectory into components at different scales. We use the coarsest scale components to approximate the global motion information and the finer scale components to partition the global motion into subtrajectories. Each subtrajectory is then modeled by a set of spatial and temporal translation invariant attributes. Motion retrieval based on subtrajectory modeling has been tested and compared against other global trajectory matching schemes to show the advantages of our approach in achieving spatio-temporal invariance properties.