Software Video Capture And Replay With Backend Event Segmentation
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Solution Overview
Problem
Existing video games, particularly esports, lack comprehensive systems for capturing, processing, and analyzing user interactions for improved viewing, monitoring, and analysis, as well as for fraud prevention and competitive oversight.
Innovation Solution
A system and method for capturing user-activity video signals, processing backend interaction data, and generating new videos using predefined rules to highlight significant events, enabling real-time and post-processing of user interactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If comprehensive video capture and processing systems are implemented for user interactions, then viewing quality and competitive oversight are improved, but system complexity and processing requirements increase
Solution Approach 1:
The system divides video processing into separate functional modules: video capture module, backend data processing module, and video generation module. Each module handles specific tasks independently, reducing overall system complexity while maintaining comprehensive monitoring capabilities.
Solution Approach 2:
A replay server acts as an intermediary between the video stream server and clients, processing backend interaction data and generating refined video content. This intermediary layer simplifies the architecture by centralizing complex processing logic in a dedicated component.
2Productivity
If real-time processing of user interaction data is performed, then spectator engagement is enhanced, but processing time and computational resources increase
Solution Approach 1:
The system captures and stores backend interaction data during gameplay in real-time, preparing it for subsequent video generation. This preliminary data collection enables rapid video creation without delaying the actual gameplay experience.
Solution Approach 2:
The replay server processes backend data and generates highlight videos at periodic intervals or upon detecting significant events, rather than continuously processing all data. This periodic processing reduces computational overhead while maintaining high spectator engagement.
3Reliability
If detailed backend interaction data is captured and processed, then fraud prevention capability is improved, but data processing complexity and storage requirements increase
Solution Approach 1:
The system extracts only the most relevant interaction data from backend logs for video generation and analysis, rather than storing and processing all raw data. This selective extraction reduces storage requirements while maintaining effective fraud detection capabilities.
Solution Approach 2:
Different levels of data processing are applied to different types of interactions: critical events receive detailed analysis for fraud prevention, while routine interactions use simplified processing. This localized quality approach optimizes both detection accuracy and resource utilization.
Data Source
AI summary
A user-activity video signal can be received. The user-activity video signal can comprise a video capture characterizing a user's interaction with a software application on a client. The software application can have an interface display space on the client and the software application can execute on the client in operation with at least one remote backend computing system. Backend user interaction data corresponding to the user's interaction with the software application as generated by the at least one remote backend computing system can be received. A new video comprising a plurality of divided segments of the user-activity video signal can be generated automatically using the backend user interaction data and a plurality of predefined rules. The new video can be provided. Related apparatus, systems, techniques, and articles are also described.