GAMING SCHEME USING GENERAL MOOD INFORMATION

• US 20140169690A1
• Filed: 12/13/2012
• Published: 06/19/2014
• Est. Priority Date: 12/13/2012
• Status: Active Grant

• Current Assignee: Atestraw Licensing LLC (IP Edge LLC)
• Original Assignee: Empire Technology Development LLC (Allied Inventors Management, LLC)
• Inventors: Miyashita, Takahiro, Satake, Satoru, Shiomi, Masahiro
• Granted Patent: US 9,302,178 B2
• Time in Patent Office: Days
• US Class Current: 382/225
• CPC Class Codes: A63F 13/10 Control of the course of the game, e.g. start, progess, end
• CPC Class Codes: A63F 13/12 involving interaction between a plurality of game devices, e.g. transmisison or distribution systems protocols for networked virtual reality, networked games H04L29/06034
• CPC Class Codes: A63F 13/213 comprising photodetecting means, e.g. cameras, photodiodes or infrared cells A63F13/219, A63F13/655 take precedence
• CPC Class Codes: A63F 13/216 using geographical information, e.g. location of the game device or player using GPS
• CPC Class Codes: A63F 13/23 for interfacing with the game device, e.g. specific interfaces between game controller and console
• CPC Class Codes: A63F 13/30 Interconnection arrangements between game servers and game devices; Interconnection arrangements between game devices; Interconnection arrangements between game servers
• CPC Class Codes: A63F 13/355 Performing operations on behalf of clients with restricted processing capabilities, e.g. servers transform changing game scene into an encoded video stream for transmitting to a mobile phone or a thin client
• CPC Class Codes: A63F 13/45 Controlling the progress of the video game
• CPC Class Codes: A63F 13/46 Computing the game score
• CPC Class Codes: A63F 13/52 involving aspects of the displayed game scene
• CPC Class Codes: A63F 13/65 automatically by game devices or servers from real world data, e.g. measurement in live racing competition
• CPC Class Codes: A63F 13/822 Strategy games; Role-playing games A63F13/825, A63F13/828 take precedence
• CPC Class Codes: A63F 13/95 Storage media specially adapted for storing game information, e.g. video game cartridges
• CPC Class Codes: A63F 2300/1093 using visible light
• CPC Class Codes: A63F 2300/535 for monitoring, e.g. of user parameters, terminal parameters, application parameters, network parameters
• CPC Class Codes: A63F 2300/5546 using player registration data, e.g. identification, account, preferences, game history
• CPC Class Codes: A63F 2300/6045 for mapping control signals received from the input arrangement into game commands

Abstract

Technologies are generally described for an general mood adding scheme in a cloud-based game system. In some examples, a method performed under control of a computing device may include receiving from a raw database at least one set of facial expression data, each of the at least one set of facial expression data being accompanied by time information and location information, clustering a geographic area to form at least one cluster based at least in part on the at least one set of facial expression data, and storing the at least one cluster in a map database corresponding to the area.

Claims

1. A method performed under control of a computing device, comprising:

receiving from a raw database at least one set of facial expression data, each of the at least one set of facial expression data being accompanied by time information and location information;

clustering a geographic area to form at least one cluster based at least in part on the at least one set of facial expression data; and

storing the at least one cluster in a map database corresponding to the geographic area.

2. The method of claim 1, wherein each of the at least one set of facial expression data is obtained from at least one image, and the at least one image is captured by a camera at a time corresponding to the time information and at a location corresponding to the location information.

3. The method of claim 1, wherein each of the at least one set of facial expression data is obtained from at least one image, and the at least one image is captured by a camera for a predetermined period corresponding to the time information and at a location corresponding to the location information.

4. The method of claim 1, wherein the at least one cluster includes general mood information, and the general mood information is one that reveals an emotion.

5. The method of claim 1, wherein the clustering includes a spatiotemporal clustering, and each of the at least one cluster includes temporal information and spatial information within the geographic area.

6. The method of claim 5, wherein the storing includes attaching each of the at least one cluster to the map database based at least in part on the temporal information and the spatial information.

7. The method of claim 1, further comprising:

receiving from the raw database at least one external factor; and

storing the at least one external factor in the map database.

8. The method of claim 7, wherein each of the at least one external factor includes at least one of population density, weather conditions and event information.

9. The method of claim 1, wherein at least one of the raw database and the map database is stored in a cloud data center.

10. A method performed under control of a computing device, comprising:

receiving at least one image captured by at least one camera located in a geographic area;

obtaining at least one set of facial expression data from the at least one captured image, each of the at least one set of facial expression data being accompanied by time information and location information;

clustering the geographic area to form at least one cluster based at least in part on the at least one set of facial expression data; and

storing the at least one cluster in a map database corresponding to the geographic area.

11. The method of claim 10, wherein the at least one cluster includes general mood information, and the general mood information is one that reveals an emotion.

12. The method of claim 10, wherein the clustering includes a spatiotemporal clustering, and each of the at least one cluster includes temporal information and spatial information within the geographic area.

13. The method of claim 12, wherein the storing includes attaching each of the at least one cluster to the map database based at least in part on the temporal information and the spatial information.

14. A computing device, comprising:

a receiving unit configured to receive from a raw database at least one set of facial expression data, each of the at least one set of facial expression data being accompanied by time information and location information;

a clustering unit configured to perform a spatiotemporal clustering of a geographic area to form at least one cluster based at least in part on the at least one set of facial expression data; and

a storing unit configured to store the at least one cluster in a map database corresponding to the geographic area.

15. The computing device of claim 14, wherein each of the at least one set of facial expression data is obtained from at least one image, and the at least one image is captured by a camera at a time corresponding to the time information and at a location corresponding to the location information.

16. The computing device of claim 14, wherein the at least one cluster includes general mood information, and the general mood information is one that reveals an emotion.

17. The computing device of claim 14, wherein each of the at least one cluster includes temporal information and spatial information within the geographic area, and

wherein the storing unit further configured to attach each of the at least one cluster to the map database based at least in part on the temporal information and the spatial information.

18. The computing device of claim 14, wherein the receiving unit further configured to receive from the raw database at least one external factor, each of the at least one external factor relating to one of the at least one set of facial expression data, and

wherein the storing unit further configured to store the at least one external factor in the map database.

19. The computing device of claim 18, wherein each of the at least one external factor includes at least one of population density, weather conditions and event information.

20. The computing device of claim 14, wherein at least one of the raw database and the map database is stored in a cloud data center.

21-23. -23. (canceled)