Patent Document ID: 20160140732
Application ID: 15004371
Patent Status: 0

Claim One:
1. A computer implemented method for calibrating image data from non-overlapping cameras, the method comprising executing on a processing unit the steps of: tracking each of a plurality of individual objects distinguished within scenes of image data from each of plurality of non-overlapping cameras; performing iterative across-camera image-matching to track the movements of objects distinguished from frame data of scenes of initial ones of the cameras to subsequent-in-time frame data of scenes of other, ending ones of the cameras; determining each of a plurality of different time-delay values observed between appearances of objects matched in the scenes of pairings of the initial and ending cameras; defining a plurality of different and consecutive-in-time time-delay histogram bins within a total range of possible values of the observed time-delays, wherein the time-delay histogram bins each span consecutive subset ranges of delay times of the total range of possible values of the observed time-delays; for each matched pair of object images, entering a vote into one of the time-delay histogram bins having a subset range of delay times that comprises a delay time between an appearance of the object image in the initial camera scene and an appearance in the ending camera scene; modeling, via kernel density estimators, totals of the votes entered into each of the different time-delay histogram bins; defining a two-dimensional affinity cost matrix for associating the path connection combinations with pluralities of unique camera pairing entries, wherein the matrix is organized on a first dimension defined by each of a plurality of the non-overlapping cameras as initial cameras for a possible path of motion of the tracked objects between respective camera scenes, and on a remainder second dimension defined by each of the non-overlapping cameras as an ending camera for the possible path of motion of the tracked objects between respective camera scenes; and for each of the cost matrix unique camera pairing entries, determining an affinity cost as a sum-total of the kernel density estimator model totals of all intervening connected cameras for the determined path connections that link the initial and ending cameras.