Automatic Canonical Digital Image Selection Method and Apparatus

A non-transitory computer-readable storage medium tangibly encoded with computer-executable instructions, that when executed by a processor associated with a computing device, performs a method comprising:

• receiving a request for a set of canonical digital images of an entity;
• generating a number of digital image search result sets, the search result set generation comprising querying a number of digital image data stores using a number of queries, each query comprising a number of search terms;
• selecting a plurality of candidate digital images from the number of digital image search result sets, the plurality of candidate digital images being selected using a relevancy score associated with each candidate digital image of the plurality;
• analyzing each candidate digital image to detect an object of a type corresponding to the entity;
• determining an n-dimensional feature vector for a candidate digital image of the plurality using data of pixels corresponding to the object detected in the candidate digital image, the feature vector determination being performed for each candidate digital image of the plurality to determine a plurality of feature vectors;
• forming a plurality of clusters using the plurality of feature vectors, each cluster of the plurality comprising a number of feature vectors, each feature vector in each cluster corresponding to a candidate digital image of the plurality;
• and
• selecting a set of candidate digital images for the set of canonical digital images using a number of clusters of the plurality, the candidate digital image selection comprising determining, for each candidate digital image with a corresponding feature vector belonging to a cluster of the number of clusters, a measure of quality based on at least one consideration of quality, each candidate digital image of the set of candidate digital images having a higher measure of quality relative to the measure of quality associated with each unselected candidate digital image.

A computing device comprising:

• a processor;
• a non-transitory storage medium for tangibly storing thereon program logic for execution by the processor, the program logic comprising:
• receiving logic executed by the processor for receiving a request for a set of canonical digital images of an entity;
• generating logic executed by the processor for generating a number of digital image search result sets, the search result set generation comprising querying a number of digital image data stores using a number of queries, each query comprising a number of search terms;
• selecting logic executed by the processor for selecting a plurality of candidate digital images from the number of digital image search result sets, the plurality of candidate digital images being selected using a relevancy score associated with each candidate digital image of the plurality;
• analyzing logic executed by the processor for analyzing each candidate digital image to detect an object of a type corresponding to the entity;
• determining logic executed by the processor for determining an n-dimensional feature vector for a candidate digital image of the plurality using data of pixels corresponding to the object detected in the candidate digital image, the feature vector determination being performed for each candidate digital image of the plurality to determine a plurality of feature vectors;
• forming logic executed by the processor for forming a plurality of clusters using the plurality of feature vectors, each cluster of the plurality comprising a number of feature vectors, each feature vector in each cluster corresponding to a candidate digital image of the plurality;
• and
• selecting logic executed by the processor for selecting a set of candidate digital images for the set of canonical digital images using a number of clusters of the plurality, the candidate digital image selection comprising determining, for each candidate digital image with a corresponding feature vector belonging to a cluster of the number of clusters, a measure of quality based on at least one consideration of quality, each candidate digital image of the set of candidate digital images having a higher measure of quality relative to the measure of quality associated with each unselected candidate digital image.