Image classification and information retrieval over wireless digital networks and the internet

• US 9,412,009 B2
• Filed: 11/21/2014
• Issued: 08/09/2016
• Est. Priority Date: 09/28/2005
• Status: Active Grant

• Current Assignee: Motorola Solutions, Inc.
• Original Assignee: 9051147 Canada Incorporated
• Inventors: Myers, Charles A., Shah, Alex
• Primary Examiner(s): PATEL, KANJIBHAI B
• Application Number:
  US14/550,206
• Publication Number:
  US 20150086086A1
• Time in Patent Office: 627 Days
• Field of Search: 382/118, 382/305, 707/705
• US Class Current: 1/1
• CPC Class Codes: G06F 16/5838 using colour
• CPC Class Codes: G06V 20/52 Surveillance or monitoring of activities, e.g. for recognising suspicious objects recognising microscopic objects G06V20/69
• CPC Class Codes: G06V 40/16 Human faces, e.g. facial parts, sketches or expressions
• CPC Class Codes: G06V 40/168 Feature extraction; Face representation
• CPC Class Codes: G06V 40/169 Holistic features and representations, i.e. based on the facial image taken as a whole
• CPC Class Codes: G06V 40/171 Local features and components; Facial parts eye characteristics G06V40/18; Occluding parts, e.g. glasses; Geometrical relationships
• CPC Class Codes: G06V 40/172 Classification, e.g. identification
• CPC Class Codes: G06V 40/173 face re-identification, e.g. recognising unknown faces across different face tracks
• CPC Class Codes: G06V 40/179 metadata assisted face recognition
• CPC Class Codes: Y10S 707/99948 Application of database or data structure, e.g. distributed, multimedia, or image

Abstract

A method and system for matching an unknown facial image of an individual with an image of a celebrity using facial recognition techniques and human perception is disclosed herein. The invention provides a internet hosted system to find, compare, contrast and identify similar characteristics among two or more individuals using a digital camera, cellular telephone camera, wireless device for the purpose of returning information regarding similar faces to the user The system features classification of unknown facial images from a variety of internet accessible sources, including mobile phones, wireless camera-enabled devices, images obtained from digital cameras or scanners that are uploaded from PCs, third-party applications and databases. Once classified, the matching person'"'"'s name, image and associated meta-data is sent back to the user. The method and system uses human perception techniques to weight the feature vectors.

Claims

1. A method for matching an unknown image with a known image, the method comprising:

receiving an unknown facial image from a video camera at an image classification server;

processing the unknown facial image at the image classification server to create a primary feature vector;

comparing the primary feature vector to a plurality of database feature vectors;

matching the primary feature vector to a database feature vector of the plurality of database feature vectors to create matched feature vectors, wherein the database feature vector is for a second facial image;

determining a perception value of the matched feature vectors; and

transmitting the second facial image based on the perception value to a video surveillance system.

2. The method according to claim 1, wherein the primary feature vector and each of the plurality of database feature vectors are based on one or more of a facial expression, a hair style, a hair color, a facial pose, an eye color, a texture of the face, a color of the face, and facial hair.

3. The method according to claim 1, wherein the image classification server comprises an input module, a transmission engine, facial recognition software, an input feed, a feature vector database, a perception engine, and an output module.

4. The method according to claim 1, wherein the perception value ranges from 0% to 100%.

5. A method for matching an unknown image with a known image, the method comprising:

receiving one or more unknown facial images of a person from a video camera at a video surveillance system including an image classification server;

processing the unknown facial images at the image classification server to create a single feature vector or multiple feature vectors;

when there are multiple feature vectors, combining the multiple features vectors into a single feature vector;

comparing the single feature vector to a plurality of database feature vectors in a database;

matching the single feature vector to a database feature vector of the plurality of database feature vectors to create matched feature vectors, wherein the database feature vector is for a known facial image stored in the database;

determining a perception value of the matched feature vectors; and

providing the known facial image based on the perception value at the video surveillance system.

6. The method of claim 5, further comprising adding the one or more unknown facial images to the database and adding the single feature vector to the database of feature vectors.

7. The method according to claim 5, wherein the single feature vector and each of the plurality of database feature vectors are based on one or more of a facial expression, a hair style, a hair color, a facial pose, an eye color, a texture of the face, a color of the face, and facial hair.

8. The method according to claim 5, wherein the plurality of factors further comprise a distance between eyes, a distance between a center of the eyes to a chin, a size and a shape of eyebrows.

9. The method according to claim 5, wherein the image classification server comprises an input module, a transmission engine, facial recognition software, an input feed, a feature vector database, a perception engine, and an output module.

10. The method according to claim 5, wherein the perception value ranges from 0% to 100%.

11. A non-transitory computer-readable medium containing instructions, which, when executed on a processor is configured to perform an operation for matching an unknown image with a known image, comprising:

receiving an unknown facial image from a video camera at an image classification server;

processing the unknown facial image at the image classification server to create a primary feature vector;

comparing the primary feature vector to a plurality of database feature vectors;

matching the primary feature vector to a database feature vector of the plurality of database feature vectors to create matched feature vectors, wherein the database feature vector is for a second facial image;

determining a perception value of the matched feature vectors; and

transmitting the second facial image based on the perception value to a video surveillance system.

12. The non-transitory computer-readable medium according to claim 11, wherein the primary feature vector and each of the plurality of database feature vectors are based on one or more of a facial expression, a hair style, a hair color, a facial pose, an eye color, a texture of the face, a color of the face, and facial hair.

13. The non-transitory computer-readable medium according to claim 11, wherein the image classification server comprises an input module, a transmission engine, facial recognition software, an input feed, a feature vector database, a perception engine, and an output module.

14. The non-transitory computer-readable medium according to claim 11, wherein the perception value ranges from 0% to 100%.

15. The non-transitory computer-readable medium according to claim 11, further comprising transmitting the perception value with the second facial image.