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Detecting and localizing multiple objects in images using probabilistic inference

  • US 8,953,888 B2
  • Filed: 02/10/2011
  • Issued: 02/10/2015
  • Est. Priority Date: 02/10/2011
  • Status: Active Grant
First Claim
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1. A computer-implemented method comprising:

  • under control of one or more processors configured with executable instructions;

    receiving an image including an unknown number of objects to be detected;

    obtaining a plurality of voting elements from the image, the plurality of voting elements placing votes on one or more hypotheses to determine one or more locations of one or more objects in the image;

    deriving a probabilistic model based at least on the plurality of voting elements; and

    ascertaining locations of a plurality of objects in the image based at least in part on the probabilistic model, the probabilistic model including a penalty factor to discourage hallucinated object detection by penalizing a number of hypotheses used to explain the unknown number of objects in the image, wherein the penalty factor increases as the number of hypotheses used to explain the unknown number of objects in the image increases.

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