Label Consistency for Image Analysis

A computer implemented method comprising:

• receiving, by the computer, a first option for a first object in an image from a first plurality of options;
• receiving, by the computer, a second option for the first object in the image from a first plurality of options;
• receiving, by the computer, a control label for a second object in the image;
• generating a first relation score between the first option and the control label based on a co-occurrence model;
• generating, by the computer, a second relation score between the second option and the control label based on the co-occurrence model;
• determining that the first relation score exceeds the second relation score;
• and
• designating the first option as a label for the first object in the image.

A computer implemented method comprising:

• receiving a first option for a first patch within an image;
• receiving a second option for a second patch within the image;
• generating a first option score for a first patch;
• generating a first relation score based on the consistency between the first option and the second option;
• and
• generating a first global score for the first patch based on the first option score and the first relation score.

A system comprising:

• a processor configured to:
• receive a first option for a first object in an image from a first plurality of options;
• receive a second option for a second object in the image from a second plurality of options;
• generate a relation score between the first option and the second option based on a co-occurrence model;
• and
• designate the first option as a label for the first object in the image based on solving a global optimization problem utilizing at least the relation score.

A system comprising:

• a processor configured to:
• receive a first option for a first object in an image from a first plurality of options;
• receive a second option for the first object in the image from a first plurality of options;
• receive a control label for a second object in the image;
• generate a first relation score between the first option and the control label based on a co-occurrence model;
• generate, by the computer, a second relation score between the second option and the control label based on the co-occurrence model;
• determine that the first relation score exceeds the second relation score;
• and
• designate the first option as a label for the first object in the image.

A system comprising:

• a processor configured to:
• receive a first option for a first patch within an image;
• receive a second option for a second patch within the image;
• generate a first option score for a first patch;
• generate a first relation score based on the consistency between the first option and the second option;
• and
• generate a first global score for the first patch based on the first option score and the first relation score.

A device comprising:

• a storage;
• and
• a processor configured to:
• receive a first option for a first object in an image from a first plurality of options;
• receive a second option for a second object in the image from a second plurality of options;
• generate a relation score between the first option and the second option based on a co-occurrence model;
• and
• designate the first option as a label for the first object in the image based on solving a global optimization problem utilizing at least the relation score.

A device comprising:

• a storage;
• and
• a processor configured to:
• receive a first option for a first object in an image from a first plurality of options;
• receive a second option for the first object in the image from a first plurality of options;
• receive a control label for a second object in the image;
• generate a first relation score between the first option and the control label based on a co-occurrence model;
• generate, by the computer, a second relation score between the second option and the control label based on the co-occurrence model;
• determine that the first relation score exceeds the second relation score;
• and
• designate the first option as a label for the first object in the image.

A device comprising:

• a storage;
• and
• a processor configured to:
• receive a first option for a first patch within an image;
• receive a second option for a second patch within the image;
• generate a first option score for a first patch;
• generate a first relation score based on the consistency between the first option and the second option;
• and
• generate a first global score for the first patch based on the first option score and the first relation score.