Image Classification And Information Retrieval Over Wireless Digital Networks And The Internet

• US 20100150410A1
• Filed: 02/17/2010
• Published: 06/17/2010
• Est. Priority Date: 09/28/2005
• Status: Active Grant

• Current Assignee: Motorola Solutions, Inc.
• Original Assignee: FaceDouble Incorporated
• Inventors: Shah, Alex, Myers, Charles A.
• Granted Patent: US 7,885,435 B2
• Time in Patent Office: Days
• US Class Current: 382/118
• CPC Class Codes: G06V 40/168 Feature extraction; Face representation
• 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: Y10S 707/99945 Object-oriented database structure processing
• CPC Class Codes: Y10S 707/99948 Application of database or data structure, e.g. distributed, multimedia, or image

Abstract

The invention provides a internet hosted system to find, compare, contrast and identify similar characteristics among two or more individuals or objects using a digital camera, cellular telephone camera, wireless device for the purpose of returning information regarding similar objects or faces to the user The system features classification of 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, or the matching object, image and associated meta-data is sent back to the user. The image may be manipulated to emphasize similar characteristics between the received facial image and the matching facial image. The meta-data sent down with the image may include sponsored links and advertisements.

Claims

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

receiving an unknown facial image of an individual from a sender computer over a network at an image classification server;

processing the unknown facial image to create a processed image;

comparing the processed image to a plurality of database processed images;

matching the processed image to a database processed image of the plurality of database processed images to create matched images, wherein the database processed image is a facial image of another individual; and

determining a perception value of the matched images.

2. The method according to claim 1 wherein the processed image is processed as a primary feature vector and the plurality of database processed images is a plurality of database feature vectors, and wherein comparing the processed image to a plurality of database processed images comprises comparing the primary feature vector to each of the plurality of database feature vectors.

3. The method according to claim 2 wherein matching the processed image to a database processed image of the plurality of database processed images to create matched images comprises selecting a database feature vector with a value that is most similar to the value of the primary feature vector.

4. The method according to claim 2 wherein comparing the processed image to a plurality of database processed images further comprises applying a statistical model based on human perception as determined by user'"'"'s votes of previous third party matched images.

5. The method according to claim 1 further comprising filtering the database processed image to provide a preferred database processed image for the matched images.

6. The method according to claim 2 wherein the primary feature vector and each of the plurality of database feature vectors are based on at least one of a plurality of factors comprising facial expression, hair style, hair color, facial pose, eye color, texture of the face, color of the face and facial hair.

7. The method according to claim 1 further comprising transmitting the matched images to the sender over a network.

8. The method according to claim 1 wherein the unknown facial image is a JPEG image.

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

11. The method according to claim 1 further comprising analyzing the unknown facial image at the image classification server by determining if a plurality of facial image factors are acceptable, the plurality of facial image factors comprising the lack of a facial image, the lack of eyes, uneven lighting, the brightness of the facial image, pose angle of the facial image, relative size of the facial image and pixel strength of the facial image.