Application Event Detection for Automatic Gaming Highlight Capture
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Solution Overview
Problem
Existing gaming systems lack the ability to automatically identify and record significant events, such as highlights, during gameplay, requiring manual intervention that can disrupt the user's experience.
Innovation Solution
A remote system analyzes input and content data to identify events, automatically recording them and providing contextual help or session commentary, using techniques like speech and object recognition.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If manual recording of gaming highlights is implemented, then recording capability is provided, but user experience is disrupted and operation complexity increases
Solution Approach 1:
The system automatically identifies and records gaming events without requiring user intervention. The event identification module autonomously analyzes game data, detects events based on predefined criteria, and triggers recording actions, allowing the system to serve itself rather than requiring manual user control.
Solution Approach 2:
The system pre-establishes event identification criteria and recording parameters before gameplay begins. By configuring event detection rules, data sources, and recording settings in advance, the system prepares the automated recording mechanism to immediately identify and capture events as they occur during gaming sessions.
2Measurement precision
If continuous monitoring of game data is performed to identify events, then event detection accuracy is improved, but energy consumption and processing load increase
Solution Approach 1:
The system applies different monitoring intensities to different game data elements. Critical events and key performance indicators receive continuous high-precision monitoring, while less important data elements are monitored at lower intensities or sampled periodically, optimizing the balance between detection accuracy and processing energy consumption.
Solution Approach 2:
The system monitors only the specific game data elements and parameters necessary for event identification rather than continuously analyzing all game data. By focusing monitoring resources on relevant partial data sets, the system achieves sufficient event detection accuracy without the excessive energy consumption of comprehensive continuous monitoring.
Data Source
AI summary
This disclosure describes, in part, techniques for identifying application events. For instance, system(s) may provide an application, such as a gaming application, by receiving input data generated by a control device and updating states of the application using the input data. The system(s) may then send, to a display device, content data representing the states of the application. While providing the application, the system(s) may analyze the input data and/or the content data in order to determine that a criterion associated with an event is satisfied. Based on the determination, the system(s) may determine that the event has occurred. As such, the system(s) may perform one or more actions associated with the event. For example, the system(s) may cause a storing of the content data representing the event, send contextual help associated with the event, or send commentary associated with the application.