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IDENTIFYING ANOMALOUS OBJECT TYPES DURING CLASSIFICATION

  • US 20110052068A1
  • Filed: 08/31/2009
  • Published: 03/03/2011
  • Est. Priority Date: 08/31/2009
  • Status: Active Grant
First Claim
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1. A computer-implemented method for identifying anomaly object types during classification of image data captured by a video camera, the method comprising:

  • receiving a micro-feature vector including multiple micro-feature values, each micro-feature value based on at least one pixel-level characteristic of a foreground patch that depicts a foreground object within the image data;

    classifying the foreground object as depicting a first object type corresponding to a first object type cluster of the object type clusters based on the micro-feature vector;

    computing a probability density function for the object type clusters;

    computing a probability density value for the micro-feature vector;

    evaluating a rareness measure of the micro-feature vector, wherein the rareness measure estimates a likelihood of observing the micro-feature vector, based on the probability density function and the probability density value; and

    identifying the foreground object as an anomaly object type when the rareness measure is below a specified threshold.

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