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Automatic classification of objects within images

  • US 7,813,561 B2
  • Filed: 08/14/2006
  • Issued: 10/12/2010
  • Est. Priority Date: 08/14/2006
  • Status: Active Grant
First Claim
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1. A method in a computing device for classifying an object of a target image, the method comprising:

  • providing classified images and an associated classification for each classified image, the associated classification indicating a classification of an object represented by the classified image, each classified image being represented by feature vectors of salient points of the image;

    providing a plurality of clusters of the salient points of the classified images, each cluster having salient points of a plurality of classified images whose feature vectors are within a threshold similarity of a representative feature vector of the cluster, each cluster having a mapping of each salient point of the cluster to the classified image that contains that salient point; and

    after the clusters have been provided,identifying target salient points of the target image;

    generating a target feature vector for each target salient point;

    identifying candidate images by, for each target salient point;

    selecting the cluster whose salient points are most similar to the target salient point as indicated by a minimum distance between a feature vector of a salient point of the cluster and the target feature vector;

    identifying near salient points of the selected cluster whose distance between the feature vector of the salient point and the target feature vector is below a threshold; and

    marking images that contain the identified near salient points as candidate images;

    identifying classified images that are most similar to the target image bycalculating a similarity between each candidate image and the target image based on similarity between feature vectors of salient points of the candidate image and the target feature vectors;

    discarding candidate images whose calculated similarity does not satisfy a threshold similarity; and

    after discarding the candidate images, filtering out candidate images whose arrangement of salient points is inconsistent with corresponding target salient points wherein the remaining candidate images are the identified classified images; and

    selecting a classification for the object of the target image based on the classifications of the identified classified images.

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