SYSTEM AND METHOD FOR RECOMMENDING BUDDIES IN SOCIAL NETWORK

• US 20130251201A1
• Filed: 03/21/2013
• Published: 09/26/2013
• Est. Priority Date: 03/22/2012
• Status: Abandoned Application

• Current Assignee: Samsung Electronics Co. Ltd.
• Original Assignee: Samsung Electronics Co. Ltd.
• Inventors: ZHOU, Lixia
• Application Number:
  US13/848,302
• Publication Number:
  US 20130251201A1
• Time in Patent Office: Days
• US Class Current: 382/103
• CPC Class Codes: G06V 20/30 in albums, collections or shared content, e.g. social network photos or video
• CPC Class Codes: G06V 40/161 Detection; Localisation; Normalisation

Abstract

A system for recommending buddies in a social network includes a data management module, a face detection and characteristics extraction module, a face matching module, a user avatar determining module, a buddy recommendation computing module and a buddy recommendation control module. The buddy recommendation control module extracts photo album data of respective users from a data management module, controls the face detection and characteristics extraction module to perform face detection and extraction of face characteristics data, and constructs a photo album face characteristics table comprising extracted face characteristics data for respective users. The buddy recommendation control module controls the user avatar determining module to determine user avatar characteristics of each user and controls the buddy recommendation computing module to generate the buddy recommendation data based on the constructed photo album face characteristics tables, user information and buddy information in the data management modules of respective users.

Claims

1. A system for recommending buddies in a network, comprising:

a data management module to manage information of a plurality of users forming the network, buddy information of the users, and photo data uploaded by the plurality of users;

a face detection and characteristics extraction module to analyze photos, to detect face areas in the photos, to extract face characteristics data from the detected face areas, and to generate a face characteristics table comprising the extracted data;

a buddy recommendation computing module to generate buddy recommendation data based on the generated face characteristics table, and user information and buddy information of the respective users in the data management module; and

a face matching module to determine whether the face characteristics data provided by the buddy recommendation computing module is matched, and to return a matching result to the buddy recommendation computing module.

2. The system of claim 1, further comprising:

a buddy recommendation control module to provide a photo uploaded by a user to the face detection and characteristics extraction module, to control the data management module to store the face characteristics data extracted by the face detection and characteristics extraction module, to control the buddy recommendation computing module to generate buddy recommendation data, and to provide at least one user with buddy recommendation information based on the buddy recommendation data.

3. The system of claim 2, further comprising:

a user avatar determining module to determine for each user, user avatar characteristics based on the photo album characteristics table, wherein the buddy recommendation control module controls the data management module to store in the user information the user avatar characteristics extracted by the user avatar determining module.

4. The system of claim 3, wherein the buddy recommendation control module deletes repeated face characteristics data from the photo album face characteristics table.

5. The system of claim 1, wherein the buddy recommendation computing module matches each face characteristics data in the photo album face characteristics table with avatar characteristics of respective users, and recommends a user to other users having the matched user avatar information, every time the face matching module returns a positive matching result and the matched user avatar characteristics do not belong to the user or any buddy of the user.

6. The system of claim 3, wherein if the user avatar determining module determines no preset avatar photo has been set in the photo album data of a first user, the user avatar determining module uses the face characteristics data with the highest count extracted from the photo album characteristics table of the first user as the user avatar characteristics of the first user.

7. The system of claim 1, further comprising:

a security control module to provide selected photos from among the photo data uploaded by a user, which are authorized by the user to the face detection and characteristics extraction module.

8. The system of claim 1, wherein the face detection and characteristics extraction module uses at least one of the following to perform face detection:

a template match model, a skin color model, an active appearance model (AAM), a support vector machine (SVM) model and an Adaboost model.

9. The system of claim 1, wherein the face detection and characteristics extraction module uses at least one of template-based characteristics extraction, characteristics extraction based on algebraic methods, characteristics extraction based on flexibility matching, characteristics extraction based on a neural network, and characteristics extraction based on a wavelet multi-resolution to extract face characteristics.

10. The system of claim 1, wherein the face matching module performs matching of face characteristics data using a principal component analysis method.

11. The system of claim 1, wherein the buddy recommendation control module controls the face detection and characteristics extraction module to detect face characteristics of at least two users included in a single photo other than a third user included in the single photo, checks buddy information through the data management module, and performs buddy recommendation for the at least two users other than the third user.

12. The system of claim 1, wherein the buddy recommendation control module controls the face detection and characteristics extraction module to detect face characteristics of a second user while excluding a first user included in a first photo, and to detect face characteristics of a third user included in a second photo while excluding the first user included in the second photo, checks buddy information through the data management module, and performs buddy recommendation for the second and third users.

13. A method for recommending buddies in a social network, comprising:

generating data of each user in the social network;

analyzing a photo of each user and extracting face characteristics from the face area of each person; and

generating buddy recommendation data by using the extracted face characteristics.

14. The method of claim 13, further comprising:

analyzing a photo of each user and determining user avatar characteristics of the users.

15. A method for recommending buddies in a network comprising:

analyzing a photo in the photo album of each user in the network, detecting a face area in the photo, extracting face characteristics data from the face area of each person and constructing a photo album face characteristics table comprising face characteristics data extracted from the photos of the photo album;

determining face characteristics data extracted from an avatar photo of each user in the network and storing the determined avatar characteristics in a user information table as an user avatar characteristics item;

matching each face characteristics data in the photo album face characteristics table of a first user with the user avatar characteristics of each user in the network one by one, by using the stored user information and buddy information of respective users; and

generating buddy recommendation data when the matched user avatar does not belong to the first user or any buddy of the first user.

16. The method of claim 15, wherein the photo album face characteristics table is stored in a database for each user.

17. The method of claim 15, further comprising counting each face characteristics data in the photo album face characteristics table of each user and deleting repeated face characteristics data from the photo album face characteristics table of each user.

18. The method of claim 15, further comprising

matching each face characteristics data in the photo album face characteristics table of the first user with each face characteristics data in the photo album face characteristics table of all other users one by one, and generating buddy recommendation data.

19. The method of claim 15, wherein, the buddy recommendation data comprise different contents.

20. The method of claim 15, wherein the buddy recommendation data comprise photo information extracted from the matched face avatar characteristics data.

21. The method of claim 15, wherein, if it is determined that there is no designated avatar photo in the photo album data of a user, determining the face characteristics data with the highest count extracted from the photo album characteristics table of said user as the user avatar characteristics of said user.

22. The method of claim 15, further comprising:

receiving information from a user regarding authorization for analysis and detection with respect to one or more photos in the photo album data of the said user.

23. The method of claim 15, wherein at least one of the following modules is used to perform face detection:

a template match model, a skin color model, an active appearance model (AAM), a support vector machine (SVM) model and an Adaboost model.

24. The method of claim 15, wherein at least one of the following methods is used to perform face characteristics extraction:

template-based characteristics extraction, characteristics extraction based on algebraic methods, characteristics extraction based on flexibility matching, characteristics extraction based on a neural network, and characteristics extraction based on a wavelet multi-resolution.

25. The method claim 15, further comprising:

performing match of face characteristics data using a principal component analysis method.

26. A server to provide buddy recommendations for users in a network, comprising:

a face detection and characteristics extraction module to analyze photos uploaded by users to the network, to extract face characteristics data, and to generate a face characteristics table comprising the extracted data for each user;

a user avatar determining module to determine user avatar characteristics of each user;

a face matching module to perform a first process by determining whether face characteristics data in a photo album face characteristics table of a first user matches with user avatar characteristics of at least one second user other than buddies of the first user; and

a buddy recommendation computing module to generate buddy recommendation data for the first user and the at least one second user, if a positive matching result is obtained in the first process.

27. The server of claim 26, wherein:

the face matching module performs a second process by determining whether face characteristics data stored in the photo album face characteristics table of the first user matches with face characteristics data stored in a photo album face characteristics table of at least one second user other than buddies of the first user; and

the buddy recommendation computing module generates buddy recommendation data for the first user and the at least one second user, if a positive matching result is obtained in the second process.

28. The server of claim 26, further comprising:

a buddy recommendation control module to delete face characteristics data matching the at least one second user from the photo album face characteristics table of the first user, in response to the first user adding the at least one second user as a buddy.