Real-Time Tracking Based on Dense Calibrated Camera Coverage

A tracking system, comprising:

• an interface, configured to receive images acquired by a plurality of video cameras installed in a region;
• a memory, configured to store calibration data that specifies geometrical positions and orientations of respective Fields-Of-View (FOVs) of the cameras;
• and
• one or more processors, configured to, based on the images and the calibration data, distinguish between multiple individuals present in the region, and track geometrical paths taken by the individuals in the region by:
• calculating multiple tracklets, each tracklet defining a geometrical path of a given individual in a 2D coordinate system of a given camera over a time segment;
• forming multiple clusters, each cluster comprising a set of one or more tracklets that (i) originate from one or more different cameras, (ii) occur in a given time segment, and (iii) are estimated to represent a same individual, including, for a given time segment, forming the clusters in a clustering process having at least first and second phases, by:
• (i) assigning one or more pairs of tracklets to the first phase of the clustering process, according to a first clustering metric, (ii) clustering the pairs assigned to the first phase, the clustering being performed in accordance with a second clustering metric that is different from the first clustering metric, and (iii) after clustering the pairs assigned to the first phase, proceeding to the second phase of the clustering process, including clustering one or more other pairs in accordance with the second clustering metric;
• and
• deriving the geometrical paths from the clusters.

A tracking system, comprising:

• an interface, configured to receive images acquired by a plurality of video cameras installed in a region;
• a memory, configured to store calibration data that specifies geometrical positions and orientations of respective Fields-Of-View (FOVs) of the cameras;
• and
• one or more processors, configured to, based on the images and the calibration data, distinguish between multiple individuals present in the region, and track geometrical paths taken by the individuals in the region, including:
• defining, for a given camera, based on the calibration data, effective image boundaries that exclude image portions exceeding a defined distance criterion relative to the given camera;
• and
• distinguishing between the individuals and calculating the geometrical paths based only on content falling within the effective image boundaries.

A tracking system, comprising:

• an interface, configured to receive images acquired by a plurality of video cameras installed in a region;
• a memory, configured to store calibration data that specifies geometrical positions and orientations of respective Fields-Of-View (FOVs) of the cameras;
• and
• one or more processors, configured to, based on the images and the calibration data:
• distinguish between multiple individuals present in the region, including deciding that a given individual is observed consistently in the images by applying a defined spatiotemporal consistency criterion;
• and
• track geometrical paths taken by the individuals in the region.

A tracking system, comprising:

• an interface, configured to receive images acquired by a plurality of video cameras installed in a region;
• a memory, configured to store calibration data that specifies geometrical positions and orientations of respective Fields-Of-View (FOVs) of the cameras;
• and
• one or more processors, configured to, based on the images and the calibration data, distinguish between multiple individuals present in the region, and track geometrical paths taken by the individuals in the region, including:
• calculating a first 3D position for a first time interval, based on two or more first 2D tracks having respective identifiers;
• calculating a second 3D position for a second time interval, based on two or more second 2D tracks having respective identifiers;
• and
• associating the first and second 3D positions with a same individual, in response to finding that the first 2D tracks and the second 2D tracks share at least one common identifier.

A tracking system, comprising:

• an interface, configured to receive images acquired by a plurality of video cameras installed in a region;
• a memory, configured to store calibration data that specifies geometrical positions and orientations of respective Fields-Of-View (FOVs) of the cameras;
• and
• one or more processors, configured to, based on the images and the calibration data, distinguish between multiple individuals present in the region, track geometrical paths taken by the individuals in the region, and identify, based on the geometrical paths, a group of two or more individuals that are associated with one another.