Automatically mining person models of celebrities for visual search applications

Claim 2

A computer-implemented method of automatic face recognition, comprising: obtaining a name list from one or more articles, wherein the name list includes a name for each person in a group of persons; obtaining a collection of images for each person in the group using the name of that person; selecting, from the collection of images for each person in the group, a set of representative images for that person, each of the representative images being deemed as having a highest score amongst the collection with regard to a depiction of a headshot of that person; wherein selecting the set of representative images includes: determining a first set of one or more images from the collection which are deemed duplicative based on comparing images of the collection with other images of the collection; determining a second set of one or more images from the collection which match to an image in a collection of images for another person in the group; and determining, from a remainder of the collection which excludes the first set and the second set, one or more images which are considered to be outliers as compared to a remainder of images in the collection, in order to select the set of representative images.

Claim 3

The computer-implemented method of claim 1 , further comprising filtering the one or more articles to retain only articles that contain names of people.

Claim 4

The computer-implemented method of claim 1 , wherein selecting the set of representative images includes performing iterative binary clustering.

Claim 5

The computer-implemented method of claim 1 , wherein determining the first set of one or more images from the collection includes performing intra-model analysis, and wherein determining the second set of one or more images from the collection includes performing inter-model analysis, and wherein performing the inter-model analysis is performed after the intra-model analysis.

Claim 6

The computer-implemented method of claim 1 , further comprising ranking a set of names from the name list based on a quantity in the set of representative images of each person associated with one of the names in the set of names.

Claim 7

The computer-implemented method of claim 1 , further comprising detecting a feature vector for one or more images in the set of representative images of the one or more persons in the group.

Claim 8

The computer-implemented method of claim 6 , wherein detecting the feature includes identifying a facial feature location within the one or more images in the set of representative images of the one or more persons in the group.

Claim 11

The system of claim 8 , further comprising a recognizer configured to determine whether an input image depicts a person associated with a particular name in the name list based on the set of representative images for that person.

Claim 12

The system of claim 8 , wherein the name list generator further comprises a name ranker configured to rank the one or more names in the name list based on a quantity in the set of representative images of each person in the name list.

Claim 13

The system of claim 8 , wherein the face signature detector obtains the collection of images for each person in the group using a feature detector to detect face images based on Gabor wavelets.

Claim 14

The system of claim 8 , wherein the face signature detector obtains the collection of images for each person in the group using a feature detector to detect face images based on a facial feature location within the one or more face images.

Claim 15

The system of claim 9 , wherein the recognizer determines that there is no matching name associated with a given image.

Claim 16

The computer-implemented method of claim 1 , further comprising performing recognition of an input image using the set of representative images for one or more of the persons in the group.

Claim 17

A non-transitory computer-readable medium that stores instructions, including instructions that when executed by one or more processors, cause the one or more processors to perform operations that comprise: obtaining a name list from one or more articles, wherein the name list includes a name for each person in a group of persons; obtaining a collection of images for each person in the group using the name of that person; selecting, from the collection of images for each person in the group, a set of representative images for that person, each of thSe representative images being deemed as having a highest score amongst the collection with regard to a depiction of a headshot of that person; wherein selecting the set of representative images includes: determining a first set of one or more images from the collection which are deemed duplicative based on comparing images of the collection with other images of the collection; determining a second set of one or more images from the collection which match to an image in a collection of images for another person in the group; and determining, from a remainder of the collection which excludes the first set and the second set, one or more images which are considered to be outliers as compared to a remainder of images in the collection, in order to select the set of representative images.

Claim 18

A non-transitory computer-readable medium that stores instructions, including instructions that when executed by one or more processors, cause the one or more processors to perform operations that comprise: obtaining a name list from one or more articles, wherein the name list includes a name for each person in a group of persons; obtaining a collection of images for each person in the group using the name of that person; selecting, from the collection of images for each person in the group, a set of representative images for that person, each of thSe representative images being deemed as having a highest score amongst the collection with regard to a depiction of a headshot of that person; wherein selecting the set of representative images includes: determining a first set of one or more images from the collection which are deemed duplicative based on comparing images of the collection with other images of the collection; determining a second set of one or more images from the collection which match to an image in a collection of images for another person in the group; and determining, from a remainder of the collection which excludes the first set and the second set, one or more images which are considered to be outliers as compared to a remainder of images in the collection, in order to select the set of representative images.

Claim 19

The non-transitory computer-readable medium of claim 15 , further comprising instructions for filtering the one or more articles to retain only articles that contain names of people.

Claim 20

The non-transitory computer-readable medium of claim 15 , wherein instructions for determining the set of representative images includes instructions for performing iterative binary clustering.

Claim 21

The non-transitory computer-readable medium of claim 15 , wherein instructions for determining the first set of one or more images from the collection includes instructions for performing intra-model analysis, and wherein instructions for determining the second set of one or more images from the collection includes instructions for performing inter-model analysis, and wherein performing the inter-model analysis is performed after the intra-model analysis.

Claim 22

The non-transitory computer-readable medium of claim 15 , further comprising instructions for ranking a set of names from the name list based on a quantity of associated representative images of each person associated with one of the names in the set of names.

Claim 23

The non-transitory computer-readable medium of claim 15 , further comprising instructions for performing recognition of an input image using the set of representative images for one or more of the persons in the group.