Method and system for face detection in digital images

Claim 2

A digital image processing method for detecting faces in a digital color image, said method comprising the steps of: providing a distributed face detection system having N complementary classifiers, wherein the classifiers are complementary in a frequency domain; selecting classifier parameters for the complementary classifiers from a plurality of different parameter generating sources, at least one of which is controllable by human input; reconfiguring the complementary classifiers in the distributed face detection system according to the selected classifier parameters, such that any desired combination of only M of the N complementary classifiers are involved in face detection, wherein M and N are integers, M is less than N, and M is greater than zero; and detecting faces using the M complementary classifiers in the distributed face detection system; wherein the step of providing a distributed face detection system having complementary classifiers comprises the steps of: constructing one or more classifiers having high execution speed and featuring operation in one portion of the frequency spectrum of the digital image, and constructing one or more classifiers having high accuracy and featuring operation in another portion of the frequency spectrum of the digital image; and wherein the step of constructing one or more classifiers having high accuracy and featuring operation in another portion of the frequency spectrum of the digital image comprises steps of: constructing a cascaded classifier, and constructing a Bayesian classifier.

Claim 3

The method as claimed in claim 1 wherein the step of constructing one or more classifiers having high execution speed and featuring operation in one portion of the frequency spectrum of the digital image comprises the step of constructing a grid pattern classifier.

Claim 4

A digital image processing method for detecting faces in a digital color image, said method comprising the steps of: providing a distributed face detection system having N complementary classifiers, wherein the classifiers are complementary in a frequency domain; selecting classifier parameters for the complementary classifiers from a plurality of different parameter generating sources, at least one of which is controllable by human input; reconfiguring the complementary classifiers in the distributed face detection system according to the selected classifier parameters, such that only M of the N complementary classifiers are involved in face detection, wherein M and N are integers, M is less than N, and M is greater than zero; and detecting faces using the M complementary classifiers in the distributed face detection system, wherein the step of providing a distributed face detection system having complementary classifiers comprises the steps of: constructing one or more classifiers having high execution speed and featuring operation in one portion of the frequency spectrum of the digital image; and constructing one or more classifiers having high accuracy and featuring operation in another portion of the frequency spectrum of the digital image, wherein the step of constructing one or more classifiers having high execution speed and featuring operation in one portion of the frequency spectrum of the digital image comprises the step of constructing a grid pattern classifier, and wherein the step of constructing a grid pattern classifier comprises the steps of: generating a mean grid pattern element (MGPe) image from a plurality of sample face images; generating an integral image from the digital color image; locating faces in the digital color image by using the integral image to perform a correlation test between the mean grid pattern element (MGPe) image and the digital color image at a plurality of effective resolutions by reducing the digital color image to a plurality of grid pattern element images (GPes) at different effective resolutions and correlating the MGPe with the GPes.

Claim 5

A digital image processing method for detecting faces in a digital color image, said method comprising the steps of: providing a distributed face detection system having N complementary classifiers, wherein the classifiers are complementary in a frequency domain; selecting classifier parameters for the complementary classifiers from a plurality of different parameter generating sources, at least one of which is controllable by human input; reconfiguring the complementary classifiers in the distributed face detection system according to the selected classifier parameters, such that only M of the N complementary classifiers are involved in face detection, wherein M and N are integers, M is less than N, and M is greater than zero; and detecting faces using the M complementary classifiers in the distributed face detection system, wherein the step of providing a distributed face detection system having complementary classifiers comprises the steps of: constructing one or more classifiers having high execution speed and featuring operation in one portion of the frequency spectrum of the digital image; and constructing one or more classifiers having high accuracy and featuring operation in another portion of the frequency spectrum of the digital image, wherein the step of constructing one or more classifiers having high execution speed and featuring operation in one portion of the frequency spectrum of the digital image comprises the step of constructing a grid pattern classifier, and wherein the step of constructing a grid pattern classifier comprises the steps of: generating a mean grid pattern element (MGPe) image from a plurality of sample face images; generating an integral image from the digital color image; locating faces in the digital color image by using the integral image to perform a correlation test between the mean grid pattern element (MGPe) image and the digital color image at a plurality of effective resolutions by reducing the digital color image to a plurality of grid pattern element images (GPes) at different effective resolutions and correlating the MGPe with the GPes.

Claim 6

The method as claimed in claim 3 wherein the step of generating a mean grid pattern element (MGPe) image comprises the steps of: collecting sample face images; generating a mean face image from the sample face images; selecting a grid pattern (GP); and reducing the resolution of the mean face image to the resolution of the selected grid pattern (GP) by averaging.

Claim 7

The method as claimed in claim 4 wherein the grid pattern is regular.

Claim 8

The method as claimed in claim 4 wherein the grid pattern is irregular.

Claim 9

The method as claimed in claim 6 wherein the step of selecting an irregular grid pattern comprises determining a plurality of different size grid cells that cover major features including eyes, nose, mouth, forehead, and cheek of the mean face image.

Claim 10

The method as claimed in claim 5 wherein the step of selecting a regular grid pattern comprises computing a distance e 1 between two eye centers of the mean face image; computing a center position c between two eye centers; using e 1 and c to determine a region that contains M by N grid cells with each cell having m by n pixels.

Claim 11

A digital image processing method for detecting faces in a digital color image, said method comprising the steps of: providing a distributed face detection system having complementary classifiers, wherein the classifiers are complementary in a frequency domain; selecting classifier parameters for the complementary classifiers from a plurality of different parameter generating sources, at least one of which is controllable by human input; reconfiguring the complementary classifiers in the distributed face detection system according to the selected classifier parameters; and detecting faces using the distributed face detection system, wherein the step of providing a distributed face detection system having complementary classifiers comprises the steps of: constructing one or more classifiers having high execution speed and featuring operation in one portion of the frequency spectrum of the digital image; and constructing one or more classifiers having high accuracy and featuring operation in another portion of the frequency spectrum of the digital image, wherein the step of constructing one or more classifiers having high execution speed and featuring operation in one portion of the frequency spectrum of the digital image comprises the step of constructing a grid pattern classifier, and wherein the step of generating an integral image further comprises the steps of: replacing non-skin-color pixels with black to produce an image C having skin color pixels; replacing non-face-shaped clusters with black to produce an image E having skin colored face shaped clusters; labeling clusters of skin colored face shaped clusters; and generating the integral image from each cluster of the image E.

Claim 12

A digital image processing method for detecting faces in a digital color image, said method comprising the steps of: providing a distributed face detection system having complementary classifiers, wherein the classifiers are complementary in a frequency domain; selecting classifier parameters for the complementary classifiers from a plurality of different parameter generating sources, at least one of which is controllable by human input; reconfiguring the complementary classifiers in the distributed face detection system according to the selected classifier parameters; and detecting faces using the distributed face detection system, wherein the step of providing a distributed face detection system having complementary classifiers comprises the steps of: constructing one or more classifiers having high execution speed and featuring operation in one portion of the frequency spectrum of the digital image; and constructing one or more classifiers having high accuracy and featuring operation in another portion of the frequency spectrum of the digital image, wherein the step of constructing one or more classifiers having high execution speed and featuring operation in one portion of the frequency spectrum of the digital image comprises the step of constructing a grid pattern classifier, and wherein the step of generating an integral image further comprises the steps of: replacing non-skin-color pixels with black to produce an image C having skin color pixels; replacing non-face-shaped clusters with black to produce an image E having skin colored face shaped clusters; labeling clusters of skin colored face shaped clusters; and generating the integral image from each cluster of the image E.

Claim 13

The method claimed in claim 9 further comprising the steps of: eliminating faces that contain more than a predetermined percentage of black pixels; and merging faces that substantially overlap.

Claim 14

The method claimed in claim 9 wherein the step of replacing non-face-shaped clusters comprises the steps of: clustering skin-color pixels in image C into clusters; applying a morphological opening and closing processes to skin-colored pixel clusters; and replacing the pixels of a cluster with black if it does not meet a geometrical criterion for a face, resulting in an image E, and wherein the step of labeling skin-colored clusters comprises the step of generating a linked list of sets of parameters including a starting position, width, and height that defines regions containing a cluster of skin-colored pixels.

Claim 15

The method as claimed in claim 1 wherein the step of selecting classifier parameters for the complementary classifiers from a plurality of different parameter generating sources comprises the steps of: providing a constant parameter generator; and providing a controllable parameter generator.

Claim 16

The method as claimed in claim 1 wherein the step of reconfiguring the complementary classifiers in the distributed face detection system according to the selected classifier parameters comprises the steps of: providing commands to individual classifiers; and directing the input digital image to different classifiers in accordance with the commands.

Claim 17

A computer readable storage medium having instructions stored therein for causing a computer to perform the method of claim 1 .

Claim 18

A digital image processing method for detecting faces in a digital color image, said method comprising the steps of: providing a distributed face detection system having N complementary classifiers, wherein the classifiers are complementary in a frequency domain and comprise one or more classifiers having high execution speed and featuring operation in one portion of the frequency spectrum of the digital image, and one or more classifiers having high accuracy and featuring operation in another portion of the frequency spectrum of the digital image; providing classifier parameters for the complementary classifiers from a plurality of different parameter generating sources dependent upon conditions of he digital image; and detecting faces using any desired combination of only M of the N complementary classifiers in the distributed face detection system, wherein M and N are integers, M is less than N, and M is greater than zero; wherein the one or more classifiers having high accuracy and featuring operation in another portion of the frequency spectrum of the digital image are provided by: constructing a cascaded classifier, and constructing a Bayesian classifier.

Claim 19

A digital image processing method for detecting faces in a digital color image, said method comprising the steps of: providing a distributed face detection system having N complementary classifiers, wherein the classifiers are complementary in a frequency domain and comprise one or more classifiers having high execution speed and featuring operation in one portion of the frequency spectrum of the digital image, and one or more classifiers having high accuracy and featuring operation in another portion of the frequency spectrum of the digital image; providing classifier parameters for the complementary classifiers from a plurality of different parameter generating sources dependent upon conditions of he digital image; and detecting faces using any desired combination of only M of the N complementary classifiers in the distributed face detection system, wherein M and N are integers, M is less than N, and M is greater than zero; wherein the one or more classifiers having high accuracy and featuring operation in another portion of the frequency spectrum of the digital image are provided by: constructing a cascaded classifier, and constructing a Bayesian classifier.

Claim 20

The method as claimed in claim 15 wherein the one or more classifiers having high execution speed and featuring operation in one portion of the frequency spectrum of the digital image are provided by constructing a grid pattern classifier.

Claim 21

The method as claimed in claim 15 wherein the step of providing classifier parameters for the complementary classifiers from a plurality of different parameter generating sources comprises the steps of: providing a constant parameter generator; and providing a controllable parameter generator.

Claim 22

A computer readable storage medium having instructions stored therein for causing a computer to perform the method of claim 15 .

Claim 23

A digital image processing system for detecting faces in a digital color image, said system comprising: a distributed face detection system having N complementary classifiers, wherein the classifiers are complementary in a frequency domain; a plurality of different parameter generating sources for selecting classifier parameters for the complementary classifiers, wherein at least one of the sources is controllable by human input; and means for reconfiguring the complementary classifiers in the distributed face detection system according to the selected classifier parameters, such that any desired combination of only M of the N complementary classifiers are involved in face detection, wherein M and N are integers, M is less than N, and M is greater than zero; wherein the complementary classifiers include one or more classifiers having high execution speed and featuring operation in one portion of the frequency spectrum of the digital image, and classifiers having high accuracy and featuring operation in another portion of the frequency spectrum of the digital image; and wherein the classifiers having high accuracy and featuring operation in another portion of the frequency spectrum of the digital image include a cascaded classifier and a Bayesian classifier.

Claim 24

A digital image processing system for detecting faces in a digital color image, said system comprising: a distributed face detection system having N complementary classifiers, wherein the classifiers are complementary in a frequency domain; a plurality of different parameter generating sources for selecting classifier parameters for the complementary classifiers, wherein at least one of the sources is controllable by human input; and means for reconfiguring the complementary classifiers in the distributed face detection system according to the selected classifier parameters, such that any desired combination of only M of the N complementary classifiers are involved in face detection, wherein M and N are integers, M is less than N, and M is greater than zero; wherein the complementary classifiers include one or more classifiers having high execution speed and featuring operation in one portion of the frequency spectrum of the digital image, and classifiers having high accuracy and featuring operation in another portion of the frequency spectrum of the digital image; and wherein the classifiers having high accuracy and featuring operation in another portion of the frequency spectrum of the digital image include a cascaded classifier and a Bayesian classifier.

Claim 25

The system as claimed in claim 19 wherein the one or more classifiers having high execution speed and featuring operation in one portion of the frequency spectrum of the digital image comprise a grid pattern classifier.