Spectating Support Apparatus for E-Sports Viewpoint Selection
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Solution Overview
Problem
In e-sports spectating, viewers face challenges in determining the most relevant perspective to watch during multi-player competitions in three-dimensional spaces, leading to potential missed 'must-see' scenes due to numerous player perspectives.
Innovation Solution
A spectating support apparatus and method that analyzes map data and feature parameters to identify key areas of interest for spectators, generating spectating map data that highlights crucial battle situations, allowing viewers to focus on essential game moments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple player perspectives are provided for spectating, then spectators can choose from more viewing options, but spectators may feel puzzled and miss must-see scenes due to the large number of perspectives
Solution Approach 1:
The patent introduces an intermediary system (spectating support apparatus) that processes game state data and generates recommended spectating viewpoints. This intermediary analyzes player positions, game progress, and battle situations to automatically determine and present the most valuable viewing perspectives to spectators, mediating between the multiple available perspectives and the spectator's decision-making process.
Solution Approach 2:
The system implements feedback by continuously monitoring game state data (player positions, battle situations, game progress) and using this information to dynamically adjust and update recommended viewpoints. The spectating support apparatus provides real-time feedback to spectators about which perspectives are most worth watching based on current game conditions, enabling spectators to respond appropriately to developing game situations.
2Reliability
If comprehensive game data is analyzed to identify must-see scenes, then viewing quality is improved, but system complexity increases
Solution Approach 1:
The patent segments the complex task of identifying must-see scenes into distinct functional modules: a game state data acquisition unit that collects raw data, a spectating viewpoint determination unit that processes the data, and a recommendation generation unit that outputs results. This segmentation allows each module to handle specific aspects of the analysis independently, reducing overall system complexity while maintaining comprehensive analysis capabilities.
Solution Approach 2:
The system employs self-service by automatically analyzing game state data and generating viewpoint recommendations without requiring manual intervention or complex external processing. The spectating support apparatus autonomously determines which scenes are worth watching based on predefined criteria and game data, eliminating the need for manual curation or complex human-in-the-loop systems.
Data Source
AI summary
A map data analysis unit refers to map data for a game in which a plurality of players compete in a three-dimensional space to extract positional information on each player. A feature parameter extraction unit extracts a feature parameter related to the game. A spectating area analysis unit analyzes one or more areas in a map that should be viewed by spectators, based on the positional information on each player and the feature parameter related to the game. A map data generation unit generates spectating map data by associating information indicating the area that should be viewed by spectators with the map data.