Automatic hierarchical classification using time-based co-occurrences

While a tracking system is unaware of the identity of any object it tracks, the identity remains the same for the entire tracking sequence. Our system leverages this information by accumulating joint cooccurrences of the representations within the sequence. These joint co-occurrence statistics are then used to create a hierarchical binary-tree classification of the representations. This method is useful to classify sequences as well as individual instances. We illustrate the use of this method on two separate representationsthe tracked object’s position, movement, and size; and the tracked object’s binary motion silhouettes.