Face annotation for photo management
AssigneeMicrosoft Corporation
InventorsLei Zhang, Longbin Chen, Mingjing Li, Hong-Jiang Zhang
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Abstract
Systems and methods for annotating a face in a digital image are described. In one aspect, a probability model is trained by mapping one or more sets of sample facial features to corresponding names of individuals. A face from an input data set of at least one the digital image is then detected. Facial features are then automatically extracted from the detected face. A similarity measure is them modeled as a posterior probability that the facial features match a particular set of features identified in the probability model. The similarity measure is statistically learned. A name is then inferred as a function of the similarity measure. The face is then annotated with the name.
Claims36
A method implemented by a computing device, the method comprising:
- deriving a similarity measure by integrating results from content-based image retrieval and face recognition into a Bayesian framework to obtain a maximum posterior estimation that extended face area contextual features, face appearance, and face components associated with a set of facial features match a particular set of features identified in a probability model, the probability model mapping one or more sets of sample facial features independent of any specific individual to corresponding names of individuals;
- and
- inferring a name of a particular person that corresponds to the facial features as a function of the similarity measure.
A computer-readable medium comprising computer-program instructions executable by a processor, the computer-program instructions comprising instructions for:
- training a probability model to map one or more sets of sample facial features to corresponding names of individuals;
- detecting a face in a digital image;
- extracting facial features from the face;
- modeling a similarity measure as a posterior probability that the facial features match a particular set of features identified in a probability model, the similarity measure being statistically learned;
- inferring a name as a function of the similarity measure;
- and
- annotating the face with the name.
A computing device comprising a processor and a memory, the memory comprising computer-program instructions executable by the processor, the computer-program instructions comprising instructions for:
- extracting facial features from a detected face in digital image data;
- deriving a similarity measure by integrating results from content-based image retrieval and face recognition into a Bayesian framework to obtain a maximum posterior estimation that extended face area contextual features, face appearance, and face components associated with the facial features match a particular set of features identified in a probability model, the probability model mapping one or more sets of sample facial features independent of any specific individual to corresponding names of individuals;
- and
- inferring a name as a function of the similarity measure.
A computing device comprising:
- means for deriving a similarity measure by integrating results from content-based image retrieval and face recognition into a Bayesian framework to obtain a maximum posterior estimation that extended face area contextual features, face appearance, and face components associated with a set of facial features match a particular set of features identified in a probability model, the probability model mapping one or more sets of sample facial features independent of any specific individual to corresponding names of individuals;
- and
- means for inferring a name of a particular person that corresponds to the facial features as a function of the similarity measure.
Dependencies are inferred from the claim text.