Classification and organization of consumer digital images using workflow, and face detection and recognition

• US 8,553,949 B2
• Filed: 09/04/2009
• Issued: 10/08/2013
• Est. Priority Date: 01/22/2004
• Status: Active Grant

• Current Assignee: FotoNation Limited (Adeia Inc.)
• Original Assignee: DigitalOptics Corporation Europe Limited (Adeia Inc.)
• Inventors: Steinberg, Eran, Corcoran, Peter, Prilutsky, Yury, Bigioi, Petronel, Ciuc, Mihai, Ciurel, Stefanita, Vertan, Constantin
• Primary Examiner(s): STREGE, JOHN B
• Application Number:
  US12/554,258
• Publication Number:
  US 20100066822A1
• Time in Patent Office: 1,495 Days
• Field of Search: 382/118, 382/224, 348/77
• US Class Current: 382/118
• CPC Class Codes: G06F 18/23 Clustering techniques
• CPC Class Codes: G06F 3/04842 Selection of displayed objects or displayed text elements G06F3/0482 takes precedence
• CPC Class Codes: G06V 10/763 Non-hierarchical techniques, e.g. based on statistics of modelling distributions
• CPC Class Codes: G06V 20/647 by matching two-dimensional images to three-dimensional objects
• CPC Class Codes: G06V 40/167 using comparisons between temporally consecutive images
• CPC Class Codes: G06V 40/173 face re-identification, e.g. recognising unknown faces across different face tracks

Abstract

A processor-based system operating according to digitally-embedded programming instructions performs a method including identifying a group of pixels corresponding to a face region within digital image data acquired by an image acquisition device. A set of face analysis parameter values is extracted from said face region, including a faceprint associated with the face region. First and second reference faceprints are determined for a person using reference images captured respectively in predetermined face-portrait conditions and using ambient conditions. The faceprints are analyzed to determine a baseline faceprint and a range of variability from the baseline associated with the person. Results of the analyzing are stored and used in subsequent recognition of the person in a subsequent image acquired under ambient conditions.

Claims

1. A processor-based image acquisition and processing system comprising:

an image acquisition component comprising a lens and image sensor for acquiring a digital image, and

a processing component including a processor and a memory having processor-readable code embedded therein for programming the processor to perform a method of classifying and archiving images including face regions that are acquired with an image acquisition component, wherein the method comprises;

identifying a group of pixels corresponding to a face region within digital image data acquired by the acquisition device;

extracting a set of face analysis parameter values from said face region, said set of face analysis parameter values comprising a faceprint associated with said face region that comprises a vector defined by a set of values for a set of face classifier parameters mapped into a faceprint space within one or more existing face classes or within a new face class defined as including one or more faceprints that are defined by vectors defined by a set of values that fall within a certain geometric distance of the vector defining a faceprint data range;

determining a first reference faceprint for a person using a reference image captured in predetermined face-portrait conditions;

determining a second reference faceprint for a person using a reference image captured using ambient conditions;

analyzing said first and second reference faceprints to determine a baseline faceprint and a range of variability from said baseline associated with said person; and

storing results of said analyzing and using said results in the subsequent recognition of said person in a subsequent image acquired under ambient conditions.

2. The system of claim 1, wherein the method further comprises repeating for one or more different persons.

3. The system of claim 1, wherein the method further comprising normalizing said face regions with respect to size.

4. The system of claim 1, wherein the method further comprises normalizing said face regions with respect to a standard size based on one or more distances between eyes, nose or mouth, or combinations thereof.

5. The system of claim 1, wherein the method further comprises normalizing said face regions first with respect to pose, and then with respect to orientation, and then with respect to size.

6. A method of classifying and archiving images including face regions that are acquired with an image acquisition component, wherein the method comprises:

using a processor;

identifying a group of pixels corresponding to a face region within digital image data acquired by the acquisition device;

extracting a set of face analysis parameter values from said face region, said set of face analysis parameter values comprising a faceprint associated with said face region that comprises a vector defined by a set of values for a set of face classifier parameters mapped into a faceprint space within one or more existing face classes or within a new face class defined as including one or more faceprints that are defined by vectors defined by a set of values that fall within a certain geometric distance of the vector defining a faceprint data range;

determining a first reference faceprint for a person using a reference image captured in predetermined face-portrait conditions;

determining a second reference faceprint for a person using a reference image captured using ambient conditions;

analyzing said first and second reference faceprints to determine a baseline faceprint and a range of variability from said baseline associated with said person; and

storing results of said analyzing and using said results in the subsequent recognition of said person in a subsequent image acquired under ambient conditions.

7. The method of claim 6, further comprising repeating for one or more different persons.

8. The method of claim 6, further comprising normalizing said face regions with respect to size.

9. The method of claim 6, further comprising normalizing said face regions with respect to a standard size based on one or more distances between eyes, nose or mouth, or combinations thereof.

10. The method of claim 6, further comprising normalizing said face regions first with respect to pose, and then with respect to orientation, and then with respect to size.

11. One or more non-transitory computer-readable media having code embedded therein for programming a processor to perform a method of classifying and archiving images including face regions that are acquired with an image acquisition component, wherein the method comprises:

identifying a group of pixels corresponding to a face region within digital image data acquired by the acquisition device;

extracting a set of face analysis parameter values from said face region, said set of face analysis parameter values comprising a faceprint associated with said face region that comprises a vector defined by a set of values for a set of face classifier parameters mapped into a faceprint space within one or more existing face classes or within a new face class defined as including one or more faceprints that are defined by vectors defined by a set of values that fall within a certain geometric distance of the vector defining a faceprint data range;

determining a first reference faceprint for a person using a reference image captured in predetermined face-portrait conditions;

determining a second reference faceprint for a person using a reference image captured using ambient conditions;

analyzing said first and second reference faceprints to determine a baseline faceprint and a range of variability from said baseline associated with said person;

storing results of said analyzing and using said results in the subsequent recognition of said person in a subsequent image acquired under ambient conditions.

12. The one or more computer-readable media of claim 11, wherein the method further comprises repeating for one or more different persons.

13. The one or more computer-readable media of claim 11, wherein the method further comprising normalizing said face regions with respect to size.

14. The one or more computer-readable media of claim 11, wherein the method further comprises normalizing said face regions with respect to a standard size based on one or more distances between eyes, nose or mouth, or combinations thereof.

15. The one or more computer-readable media of claim 11, wherein the method further comprises normalizing said face regions first with respect to pose, and then with respect to orientation, and then with respect to size.