Documentation |
Assign detections to tracks for multiobject tracking
[assignments,unassignedTracks,unassignedDetections] = assignDetectionsToTracks( costMatrix,costOfNonAssignment) assigns detections to tracks in the context of multiple object tracking using the James Munkres's variant of the Hungarian assignment algorithm. It also determines which tracks are missing and which detections should begin new tracks. It returns the indices of assigned and unassigned tracks, and unassigned detections. The costMatrix must be an M-by-N matrix. In this matrix, M represents the number of tracks, and N is the number of detections. Each value represents the cost of assigning the N^{th} detection to the M^{th} track. The lower the cost, the more likely that a detection gets assigned to a track. The costOfNonAssignment scalar input represents the cost of a track or a detection remaining unassigned.
[assignments,unassignedTracks,unassignedDetections] = assignDetectionsToTracks(costMatrix, unassignedTrackCost,unassignedDetectionCost) specifies the cost of unassigned tracks and detections separately. The unassignedTrackCost must be a scalar value, or an M-element vector, where M represents the number of tracks. For the M-element vector, each element represents the cost of not assigning any detection to that track. The unassignedDetectionCost must be a scalar value or an N-element vector, where N represents the number of detections.
Code Generation Support:
Compile-time
constant input: No restriction
Supports MATLAB Function
block: Yes
Code Generation Support, Usage Notes, and Limitations
[1] Miller, Matt L., Harold S. Stone, and Ingemar J. Cox, "Optimizing Murty's Ranked Assignment Method," IEEE Transactions on Aerospace and Electronic Systems, 33(3), 1997.
[2] Munkres, James, "Algorithms for Assignment and Transportation Problems," Journal of the Society for Industrial and Applied Mathematics, Volume 5, Number 1, March, 1957.