Image ranking based on attribute correlation

A system, comprising:

• a processing unit, a computer readable memory and a computer readable storage medium;
• first program instructions to train each of a plurality of image attribute detectors for one each of a plurality of different attributes that are annotated in a training dataset of images of people;
• second program instructions to learn a plurality of pair-wise correlations between each pair of the plurality of annotated attributes from the training dataset of images;
• third program instructions to search via the trained attribute detectors an input image dataset for images comprising at least one of a multi-attribute query subset plurality of the annotated attributes;
• and
• fourth program instructions to retrieve a plurality of images from the searching of the input image dataset that each comprise at least one of the query subset plurality of attributes and in response to information from the trained attribute detectors corresponding to attributes that are not a part of the query but are relevant to the query attributes as a function of the learned plurality of pair-wise correlations, the fourth program instructions further to rank the retrieved plurality of images as a function of respective total numbers of their attributes that are also within the query subset plurality of attributes;
• and
• wherein the first, second, third and fourth program instructions are stored on the computer readable storage medium for execution by the processing unit via the computer readable memory.

An article of manufacture, comprising:

• a computer readable hardware storage device having computer readable program code embodied therewith, the computer readable program code comprising instructions that, when executed by a computer processor, cause the computer processor to:
• train each of a plurality of image attribute detectors for one each of a plurality of different attributes that are annotated in a training dataset of images of people;
• learn a plurality of pair-wise correlations between each pair of the plurality of annotated attributes from the training dataset of images;
• search via the trained attribute detectors an input image dataset for images comprising at least one of a multi-attribute query subset plurality of the annotated attributes;
• retrieve a plurality of images from the searching of the input image dataset that each comprise at least one of the query subset plurality of attributes and in response to information from the trained attribute detectors corresponding to attributes that are not a part of the query but are relevant to the query attributes as a function of the learned plurality of pair-wise correlations;
• and
• rank the retrieved plurality of images as a function of respective total numbers of their attributes that are also within the query subset plurality of attributes.