Techniques for user customization in a photo management system
First Claim
1. A computer-implemented method comprising:
- receiving, by a computing device including one or more processors, a plurality of photos;
selecting, by the computing device, a first subset of the plurality of photos based on maximizing photo quality and photo diversity using a quality metric for each of the plurality of photos and a similarity matrix for the plurality of photos, the quality metric for a photo being indicative of a quality of such photo, the similarity matrix being indicative of similarity between each pair of photos of the plurality of photos, wherein the first subset of photos is selected using joint global maximizationdetermining, by the computing device, a first set of one or more clusters for the first subset of the plurality of photos using hierarchical clustering, the first set of clusters including less than or equal to all of the first subset of the plurality of photos, each of the one or more clusters in the first set of one or more clusters including one or more distinct photos from the first subset of the plurality of photos;
storing, by the computing device, the photos arranged by the first set of one or more clusters;
receiving, by the computing device, user input with respect to the first subset of the plurality of photos, the user input corresponding to at least one of adding a first specific photo from a remainder of the plurality of photos to one of the one or more clusters in the first set of one or more clusters, and deleting a second specific photo from one of the one or more clusters in the first set of one or more clusters;
adjusting, at the computing device, at least one of the quality metric and the similarity matrix based on the user input;
selecting, by the computing device, a second subset of the plurality of photos based on maximizing photo quality and photo diversity using the adjusted at least one of the quality metric and the similarity matrix;
determining, by the computing device, a second set of one or more clusters for the second subset of the plurality of photos using hierarchical clustering; and
storing, at the computing device, second subset of the plurality of photos arranged in the second set of one or more clusters.
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Abstract
A computer-implemented technique can receive a plurality of photos and automatically select a subset of the plurality of photos having a high degree of representativeness by jointly maximizing both photo quality and photo diversity to obtain a photo album. The technique can determine one or more clusters for the photo album using a hierarchical clustering algorithm, and store the photo album according to the one or more clusters. The technique can control the manner in which the photo album is displayed using the one or more clusters. The technique can adjust at least one of the one or more clusters and the automatic photo album generation based on user input. The user input can include at least one of adding, deleting, and moving a photo with respect to the one or more clusters. The technique can then re-cluster, automatically generate a new photo album, and/or adjust the presentation.
25 Citations
19 Claims
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1. A computer-implemented method comprising:
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receiving, by a computing device including one or more processors, a plurality of photos; selecting, by the computing device, a first subset of the plurality of photos based on maximizing photo quality and photo diversity using a quality metric for each of the plurality of photos and a similarity matrix for the plurality of photos, the quality metric for a photo being indicative of a quality of such photo, the similarity matrix being indicative of similarity between each pair of photos of the plurality of photos, wherein the first subset of photos is selected using joint global maximization determining, by the computing device, a first set of one or more clusters for the first subset of the plurality of photos using hierarchical clustering, the first set of clusters including less than or equal to all of the first subset of the plurality of photos, each of the one or more clusters in the first set of one or more clusters including one or more distinct photos from the first subset of the plurality of photos; storing, by the computing device, the photos arranged by the first set of one or more clusters; receiving, by the computing device, user input with respect to the first subset of the plurality of photos, the user input corresponding to at least one of adding a first specific photo from a remainder of the plurality of photos to one of the one or more clusters in the first set of one or more clusters, and deleting a second specific photo from one of the one or more clusters in the first set of one or more clusters; adjusting, at the computing device, at least one of the quality metric and the similarity matrix based on the user input; selecting, by the computing device, a second subset of the plurality of photos based on maximizing photo quality and photo diversity using the adjusted at least one of the quality metric and the similarity matrix; determining, by the computing device, a second set of one or more clusters for the second subset of the plurality of photos using hierarchical clustering; and storing, at the computing device, second subset of the plurality of photos arranged in the second set of one or more clusters.
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2. A computer-implemented method comprising:
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receiving, by a computing device including one or more processors, a plurality of photos; selecting, by the computing device, a first subset of the plurality of photos based on maximizing photo quality and photo diversity using a quality metric for each of the plurality of photos and a similarity matrix for the plurality of photos, the quality metric for a photo being indicative of a quality of such photo, the similarity matrix being indicative of similarity between each pair of photos of the plurality of photos, wherein the first subset of photos is selected using joint global maximization determining, by the computing device, a first set of one or more clusters for the first subset of the plurality of photos using hierarchical clustering, the first set of clusters including less than or equal to all of the first subset of the plurality of photos, each of the one or more clusters in the first set of one or more clusters including one or more distinct photos from the first subset of the plurality of photos; and storing, by the computing device, the photos arranged by the first set of one or more clusters. - View Dependent Claims (3, 4, 5, 6, 7, 8, 9, 10, 11)
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12. A computing device comprising:
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an input/output device configured to receive a plurality of photos; one or more processors configured to; receive a plurality of photos; select a first subset of the plurality of photos based on maximizing photo quality and photo diversity using a quality metric for each of the plurality of photos and a similarity matrix for the plurality of photos, the quality metric for a photo being indicative of a quality of such photo, the similarity matrix being indicative of similarity between each pair of photos of the plurality of to photos, wherein the first subset of photos is selected using joint global maximization determine a first set of one or more clusters for the first subset of the plurality of photos using hierarchical clustering, the first set of clusters including less than or equal to all of the first subset of the plurality of photos, each of the one or more clusters in the first set of one or more clusters including one or more distinct photos from the first subset of the plurality of photos; and store the photos arranged by the first set of one or more clusters. - View Dependent Claims (13, 14, 15, 16, 17, 18, 19)
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Specification