Multi-subject multi-camera tracking for high-density environments

A system comprising one or more processors to:

• generate one or more clusters using a plurality of representations computed based on optical image streaming data representing one or more tracked subjects within a monitored area;
• associate, based at least on trajectory tracking data, individual clusters of the one or more clusters with a respective behavior state of one or more first behavior states computed from the optical image streaming data;
• assign, using a matching algorithm, one or more second behavior states to the one or more clusters based on at least one of the individual clusters not having an associated behavior state from the one or more first behavior states;
• and
• update at least one behavior state of the one or more first behavior states or the one or more second behavior states based on behavior data represented by the plurality of representations.

A method comprising:

• generating behavior states representing behavior data for one or more tracked subjects within an environment based on clustering a plurality of representations computed from optical image streaming data representing the environment, wherein the behavior states are updated using the plurality of representations by:
• associating, based at least on trajectory tracking data, one or more clusters of the plurality of representations with one or more first behavior states computed from the optical image streaming data;
• and
• applying a matching algorithm to assign one or more second behavior states to the one or more clusters based on at least one individual cluster of the plurality of representations not having an associated behavior state from the one or more first behavior states.