Hierarchical Partition-Based Representations for Image Sequences using Trajectory Merging Criteria

This paper describes a hierarchical analysis framework for image sequences. Region merging schemes traditionally used in the construction of partition hierarchies are extended to multiple frames using trajectory merging criteria. The merging criteria assess homogeneity among features throughout the entire sequence to recursively create partitions in the spatio-temporal domain. We propose similarity measures using long-term affine and translational motion features. Furthermore, the analysis of connectivity relations and the algorithm implementation over trajectory adjacency graphs allow the generation of partition sets containing temporally consistent objects characterized by coherent motion. Lastly, we introduce the novel trajectory tree as a single, hierarchical representation of the partitions generated for the complete sequence. Experimental results are provided, illustrating the usefulness of the approach.