Identifying And Extracting Video Game Highlights

• US 20170065888A1
• Filed: 12/30/2015
• Published: 03/09/2017
• Est. Priority Date: 09/04/2015
• Status: Abandoned Application

• Current Assignee: SRI International, Inc.
• Original Assignee: SRI International, Inc.
• Inventors: Cheng, Hui
• Application Number:
  US14/984,999
• Publication Number:
  US 20170065888A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: A63F 13/497 Partially or entirely replaying previous game actions
• CPC Class Codes: A63F 2300/634 for replaying partially or entirely the game actions since the beginning of the game

Abstract

The present invention extends to methods, systems, and computer program products for identifying and extracting game video highlights. Game highlights are identified and extracted from game video recorded or streamed from video games. Game highlights are created by identifying low-level features in a game video. Then, game concepts are detected based on identified low-level features. A game concept space is created for different types of game concepts. One or more highlights are generated using the concept space based on game knowledge and/or user preference. Multiple highlights can be fused together into a compilation of highlights.

Claims

1. A method for generating highlights from a game video of a video game, the method comprising:

identifying low-level features present in the game video by applying feature detection algorithms for detecting multiple feature types, wherein the feature types include at least one of scenes, characters, actions, objects, texts, audio, items defined by the video game, and descriptions;

detecting game concepts based on the low-level features and knowledge of one or more of characteristics of the video game, each of the one or more characteristics selected from among;

a relationship, a feature, or a concept of the video game, each of the one or more characteristics selected from among;

a spatial characteristic, a temporal characteristic, or a semantic characteristic of the video game;

creating a game concept space by establishing concept types of game concepts of high interest; and

generating one or more highlights based on concepts detected in the game video and user preference.

2. The method of claim 1, wherein detecting game concepts is further based on machine learning that has established relationships between one or more of:

(a) low-level features and game concepts and (b) games concepts and game highlights.

3. The method of claim 1, further comprising fusing highlights from one or more concepts appropriately relevant to the game type to form a game highlight.

4. The method of claim 1, further comprising pre-processing the game video.

5. The method of claim 1, wherein the algorithms for detecting multiple features include at least one of:

a static visual feature detector and a dynamic feature detector.

6. The method of claim 5, wherein the static visual feature detector comprises a scale-invariant feature transform.

7. The method of claim 5, wherein the dynamic feature detector comprises a dense-trajectory based motion boundary histogram,

8. The method of claim 1, wherein concepts are tagged with a game-specific vocabulary.

9. The method of claim 8, wherein portions of the game-specific vocabulary are machine-learned.

10. The method of claim 1, comprising generating one or more highlights based on a user profile for a user that requested video highlights.

11. The method of claim 1, comprising generating one or more highlights based on metadata provided by the manufacturer of the video game.

12. A system for generating highlights from a game video of a video game, the system comprising:

one or more processors;

system memory; and

a game highlight generation engine, using the one or more processors, configured to;

identify low-level features present in the game video by applying feature detection algorithms for detecting multiple feature types;

detect game concepts based on the low-level features and knowledge of spatial/temporal relationships of the video game;

create a game concept space by establishing concept types of game concepts of high interest; and

generate one or more highlights based on concept types and user preference.

13. The system of claim 12, wherein the feature types include at least one of scenes, characters, actions, objects, texts, audio, items defined by the video game.

14. The system of claim 12, configured to detect game concepts based on machine learning that has established relationships between low-level features and game concepts.

15. The system of claim 12, configured to tag concepts with a feature-specific vocabulary.

16. The system of claim 12, wherein portions of the feature-specific vocabulary are machine-learned.

17. The system of claim 12, wherein the game highlight generation engine, using the one or more processors, is configured to generate one or more highlights based on metadata provided by the manufacturer of the video game.