Demographic analysis of facial landmarks

摘要

A facial image may be annotated with the plurality of facial landmarks. These facial landmarks may be points or regions of the face that are indicative, either alone or in combination with other facial landmarks, of at least one demographic characteristic. Demographic characteristics include, for example, age, race, and/or gender. Based on the demographic characteristic being analyzed, one or more of these facial landmarks may be selected and arranged into an input vector. Then, the input vector may be compared to one or more of the training vectors. An outcome of this comparison may involve in the given facial image being classified into a category germane to the analyzed demographic characteristic (e.g., an age range or age, a racial category, and/or a gender).

主权项

1. A method comprising:
obtaining an input vector of facial landmarks, wherein the facial landmarks of the input vector are derived from a given facial image, and wherein the facial landmarks of the input vector are identified based on their ability to represent anthropometric characteristics of the given facial image; performing, by a computing device, a weighted comparison between the input vector and each of a plurality of training vectors, wherein each training vector is mapped to at least one of a plurality of categories, wherein each training vector represents facial landmarks derived from a different respective facial image, wherein each training vector is associated with an age of an individual from whom the different respective facial image was derived, and wherein each category in the plurality of categories comprises a different age range, wherein at least some of the facial landmarks of the input vector represent aging characteristics of the given facial image, wherein the plurality of categories comprises an adult age range, and wherein at least some of the subset of the training vectors that map to the adult age range represent facial features indicative of wrinkling, hyper-pigmentation, or thinning of fat padding; based on a result of the weighted comparison, classifying the given facial image into a category of the plurality of categories; performing a second comparison of the input vector to a subset of the training vectors, wherein at least some of the subset of the training vectors map to the category of the plurality of categories in which the given facial image was classified; and based on a result of the second comparison, estimating an age of an individual from whom the given facial image was derived.