US 7,848,548 B1 · Method and system for robust demographic classification using pose independent model from sequence of face images

Abstract

The invention provides a face-based automatic demographics classification system that is robust to pose changes of the target faces and to accidental scene variables, by using a pose-independent facial image representation which comprises multiple pose-dependent facial appearance models. Given a sequence of people's faces in a scene, the two-dimensional variations are estimated and corrected using a novel machine learning based method. We estimate the three-dimensional pose of the people, using a machine learning based approach. The face tracking module keeps the identity of the person using geometric and appearance cues, where multiple appearance models are built based on the poses of the faces. Each separately built pose-dependent facial appearance model is fed to the demographics classifier, which is trained using only the faces having the corresponding pose. The classification scores from the set of pose-dependent classifiers are aggregated to determine the final face category, such as gender, age, and ethnicity.

Claims38

Dependent claims

A method for automatically performing robust and efficient demographics classification based on a sequence of facial images of people, using a pose-independent facial image representation, comprising the following steps of:

a) capturing a plurality of input images of the people by a plurality of means for capturing images,
b) detecting faces in a plurality of images captured from said means for capturing images
c) estimating a two-dimensional facial pose and three-dimensional facial pose of the detected face by employing a parallel array of multiple learning machine regressors,
d) tracking the faces to keep the identity of the person,
e) constructing multiple pose-dependent appearance models of the faces that belong to a given track, and
f) performing demographics classification based on a pose-independent face representation, wherein the method further comprises multiple pose-dependent facial appearance models built for tracking and classification, based on an estimated pose of the face, and
whereby demographic information can comprise age, gender, and ethnicity information.

4 more elements

An apparatus for automatically performing robust and efficient demographics classification based on a sequence of the facial images of people, using a pose-independent facial image representation, comprising:

a) means for capturing a plurality of input images of the people by a plurality of means for capturing images,
b) means for detecting faces in a plurality of images captured from said means for capturing images
c) means for estimating a two-dimensional facial pose and three-dimensional facial pose of the detected face by employing a parallel array of multiple learning machine regressors,
d) means for tracking the faces to keep the identity of the person,
e) means for constructing multiple pose-dependent appearance models of the faces that belong to a given track, and
f) means for performing demographics classification based on a pose-independent face representation,
wherein the apparatus further comprises means for building multiple pose-dependent facial appearance models built for tracking and classification, based on an estimated pose of the face, and
whereby demographic information can comprise age, gender, and ethnicity information.

5 more elements

Dependencies are inferred from the claim text.

Method and system for robust demographic classification using pose independent model from sequence of face images

Life of this patent

Method and system for robust demographic classification using pose independent model from sequence of face images

Life of this patent

Abstract

Claims38