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Optimal cropping of digital image based on professionalism score of subject

  • US 10,043,240 B2
  • Filed: 04/14/2016
  • Issued: 08/07/2018
  • Est. Priority Date: 04/14/2016
  • Status: Active Grant
First Claim
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1. A computerized method for automatically cropping a digital image to improve perceived professionalism of a subject of the image, the method comprising:

  • utilizing a machine learning algorithm to generate a professionalism score for the digital image, wherein the professionalism score indicates a perceived professionalism of a human depicted in the digital image, the utilizing a machine learning algorithm comprising;

    a training mode where a plurality of sample images with labeled professionalism scores are used to train a classification function in a model that produces as professionalism score as output,an analysis mode where the model is used to generate a professionalism score for the digital image; and

    using the professionalism score for the digital image as an input to a discrete variable optimization algorithm to determine an optimum cropped version of the digital image from a plurality of possible cropped versions of the digital image using the classification function.

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