CPC H04N 7/18 (2013.01) [G06V 10/25 (2022.01); G06V 10/40 (2022.01); G06V 10/46 (2022.01); G06V 10/507 (2022.01); G06V 10/473 (2022.01)] | 20 Claims |
1. A method, comprising:
identifying, via a processor, a plurality of foreground objects depicted in a sequence of video frames;
for each foreground object from the plurality of foreground objects, deriving feature data for that foreground object from each video frame from the sequence of video frames that depicts the foreground object;
generating, via the processor and based on the derived feature data of a first foreground object from the plurality of foreground objects, an object type model;
correlating, via the processor, the derived feature data of a second foreground object from the plurality of foreground objects with the object type model by mapping the derived feature data of the second foreground object to an adaptive resonance theory (ART) network; and
in response to the correlating the derived feature data for the second foreground object with the object type model, assigning an object type identifier to the second foreground object to indicate that the second foreground object is an instance of an object type associated with the object type model.
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