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SEMANTIC REPRESENTATION MODULE OF A MACHINE LEARNING ENGINE IN A VIDEO ANALYSIS SYSTEM

  • US 20140072206A1
  • Filed: 04/02/2013
  • Published: 03/13/2014
  • Est. Priority Date: 07/11/2007
  • Status: Active Grant
First Claim
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1. A method for processing data describing a scene depicted in a sequence of video frames, the method comprising:

  • receiving input data describing one or more objects detected in the scene, wherein the input data includes at least a classification for each of the one or more objects;

    identifying one or more primitive events, wherein each primitive event provides a semantic value describing a behavior engaged in by at least one of the objects depicted in the sequence of video frames and wherein each primitive event has an assigned primitive event symbol;

    generating, for one or more objects, a primitive event symbol stream which includes the primitive event symbols corresponding to the primitive events identified for a respective object;

    generating, for one or more objects, a phase space symbol stream, wherein the phase space symbol stream describes a trajectory for a respective object through a phase space domain;

    combining the primitive event symbol stream and the phase space symbol stream for each respective object to form a first vector representation of that object; and

    passing the first vector representations to a machine learning engine configured to identify patterns of behavior for each object classification from the first vector representation.

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