×

Object detection based on joint feature extraction

  • US 10,467,459 B2
  • Filed: 09/09/2016
  • Issued: 11/05/2019
  • Est. Priority Date: 09/09/2016
  • Status: Active Grant
First Claim
Patent Images

1. A computer-implemented method comprising:

  • characterizing, by at least one processor, at least one first feature from an image, including by extracting via a first feature extraction stage the at least one first feature and characterizing the image in a whole scale providing context around object regions;

    identifying a first candidate object region defined by a first bounding box in the image based on the at least one first feature, wherein the first candidate object region includes a candidate face region;

    identifying a second candidate object region defined by a second bounding box in the image based on the at least one first feature;

    determining whether the first candidate object region defined by the first bounding box is overlapped by the second candidate object region defined by the second bounding box;

    responsive to a determination that the first candidate object region defined by the first bounding box is overlapped by the second candidate object region defined by the second bounding box;

    retaining the first candidate object region and discarding the second candidate region, andcharacterizing at least one second feature from the first candidate object region based on the at least one first feature, including by extracting via a second feature extraction stage the at least one second feature and characterizing the image in a local scale, which is at the same scale as the whole scale providing information from within the first candidate object region, the first feature extraction stage and the second feature extraction stage trained based on a joint optimization objective to improve accuracy of object detection;

    responsive to a determination that the first candidate object region defined by the first bounding box is not overlapped by the second candidate object region defined by the second bounding box;

    retaining both the first and second candidate object regions, andextracting at least one second feature at the same scale of the whole scale from the first and second candidate object regions; and

    determining, based on the at least one first feature and the at least one second feature, a target object region in the image and a confidence for the determined target object region.

View all claims
  • 1 Assignment
Timeline View
Assignment View
    ×
    ×