Determining identity of a person in a digital image

A system for detecting whether a person associated with a query image is a same person associated with another image in a set of images, the system comprising:

• one or more processors;
• a database for storing the set of images and coupled to the one or more processors;
• a face identifier communicatively coupled to the one or more processors and configured to:
• generate a query feature vector for a query image, the query feature vector including features extracted from the query image;
• determine a distance between the query feature vector and each of a set of candidate feature vectors that correspond to the set of images;
• select a set of shortest distances among the determined distances;
• generate a feature vector comprising the set of shortest distances and a distribution of the set of shortest distances;
• input the feature vector to a trained model to obtain a match probability value;
• and
• responsive to the match probability value exceeding a threshold value, determine the person associated with the query image is the same person associated with an image corresponding to the candidate feature vector that has the shortest distance among the set of shortest distances.

A non-transitory computer-readable medium or media comprising a set of instructions for detecting whether a person associated with a query image in a first user profile on a first face database is a same person associated with a second image in a second user profile on a second face database, wherein execution of the set of instructions by one or more processors causes the one or more processors to perform the steps of:

• generating a query feature vector for a query image in a first user profile on a first image database, the query feature vector including features extracted from the query image;
• determining a distance between the query feature vector and each of a set of candidate feature vectors that correspond to a set of images on the second image database;
• selecting a set of shortest distances among the determined distances;
• generating a feature vector comprising the set of shortest distances and a distribution of the set of shortest distances;
• inputting the feature vector to a trained model to obtain a match probability value;
• and
• responsive to the match probability value exceeding a threshold value, determining the person associated with the query image is the same person associated with an image corresponding to the candidate feature vector that has the shortest distance among the set of shortest distances.