Abstract: Approaches are described for formation retrieval. Embodiments receive positional data, across an interval window, including a respective agent trajectory for each agent and an object trajectory for one or more objects. The interval window is partitioned into frames and, at each frame, embodiments calculate a cost of assigning a role to each agent based on one or more exemplar formations. A formation is determined by assigning a role to each agent based on the calculated cost. Each frame of the formation is compared to a corresponding frame of a stored formation, by calculating a distance between a position of each assigned role in the frame and a position of a corresponding role in the stored formation and by comparing the object trajectory for the one or more objects with a corresponding object trajectory in the stored formation. Based on the comparisons, a list of stored formations is generated.

Abstract: Approaches are described for formation retrieval. Embodiments receive positional data, across an interval window, including a respective agent trajectory for each agent and an object trajectory for one or more objects. The interval window is partitioned into frames and, at each frame, embodiments calculate a cost of assigning a role to each agent based on one or more exemplar formations. A formation is determined by assigning a role to each agent based on the calculated cost. Each frame of the formation is compared to a corresponding frame of a stored formation, by calculating a distance between a position of each assigned role in the frame and a position of a corresponding role in the stored formation and by comparing the object trajectory for the one or more objects with a corresponding object trajectory in the stored formation. Based on the comparisons, a list of stored formations is generated.