In-game data display methods, systems, devices, and media

By constructing personalized visual attention vectors and standard visual prediction models, and combining them with genetic algorithms to optimize rendering parameters, the problem of traditional game rendering methods being unable to adapt to players' visual attention is solved. This enables adaptive adjustment of rendering parameters, improving the gaming experience and information acquisition efficiency.

CN122124455APending Publication Date: 2026-06-02NEXT TECHNOLOGY (CHENGDU) CO LTD
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Patent Information

Authority / Receiving Office
CN Β· China
Patent Type
Applications(China)
Current Assignee / Owner
NEXT TECHNOLOGY (CHENGDU) CO LTD
Filing Date
2026-03-30
Publication Date
2026-06-02

AI Technical Summary

Technical Problem

Traditional game rendering methods cannot dynamically adapt to the personalized visual attention habits of different players, resulting in rendered images that fail to effectively guide players' attention to key game elements, affecting information acquisition efficiency and game experience, and relying on expensive hardware devices.

Method used

By acquiring the player's state information in the game scene, a personalized visual attention vector and a standard visual prediction model are constructed. Combined with a genetic algorithm to optimize rendering parameters, the actual visual attention distribution is brought closer to the desired distribution, thus achieving adaptive adjustment of rendering parameters.

Benefits of technology

Without requiring additional hardware support, it can adapt to the personalized attention habits of different players without changing the core game logic, effectively guiding players' attention to key game elements, improving information acquisition efficiency and game experience.

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Abstract

This application discloses a method, system, device, and medium for displaying in-game data, relating to the technical field of games. The method includes: acquiring scene state information of a target player in the current game scene, wherein the scene state information includes first state information of a target character, field-of-view parameters of a virtual camera, and second state information of multiple virtual objects within the field of view, the target character being the character controlled by the target player; performing semantic mining on the scene state information to obtain a personalized visual attention vector for the target character, and determining a standard visual attention vector corresponding to the current game scene based on the scene state information; acquiring the target player's historical scene state information, and constructing a standard visual prediction model based on the historical scene state information; and traversing a set of target rendering parameters based on the standard visual prediction model and a genetic algorithm. This application has the effect of improving the player's gaming experience.
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