Facial image bucketing with expectation maximization and facial coordinates

摘要

Facial image bucketing is disclosed, whereby a query for facial image recognition compares the facial image against existing candidate images. Rather than comparing the facial image to each candidate image, the candidate images are organized or clustered into buckets according to their facial similarities, and the facial image is then compared to the image(s) in most-likely one(s) of the buckets. The organizing uses particular selected facial features, computes distance between the facial features, and selects ones of the computed distances to determine which facial images should be organized into the same bucket.

主权项

1. A method for facial image bucketing, comprising:
analyzing each of a plurality of facial images in a candidate image set, comprising:
determining, for the each image, a location of each of a plurality of face points;computing, for the each image, a distance between the location of each of the plurality of face points; andcomputing, for the each image, a ratio for each unique pair of the computed distances; selecting, from the computed ratios for the plurality of facial images, at least one particular one of the computed face ratios; clustering the facial images in the candidate image set into a plurality of buckets using the selected at least one particular one of the computed face ratios, comprising iteratively computing a mean and a standard deviation, according to the at least one particular one of the computed face ratios, for each of at least one image to be included in each of the plurality of buckets until achieving convergence; and performing a query for a query facial image by comparing the query facial image only to images clustered into a selected subset of the plurality of buckets.