Game Skill Motion Customization Using User Skeleton Tracking
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Solution Overview
Problem
Current game services struggle to reflect a user's personality through the skill motions of game characters, as these motions are predefined by developers and lack customization options.
Innovation Solution
A method and server system that generates skill motion sequence data based on user-provided image data, allowing users to customize skill motions and effects, including extracting skeletons, tracking feature points, and applying user-controlled adjustments to create personalized game character movements and effects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If skill motions are predefined by developers, then game development efficiency is improved, but user customization capability deteriorates
Solution Approach 1:
The system copies motion data from real-world images/videos to create skill motions for game characters. Users can record their own motions and have them automatically converted into game character animations, enabling customization without manual animation creation. This resolves the contradiction by allowing predefined motions for efficiency while enabling user-generated custom motions through automated copying from image data.
Solution Approach 2:
Users can independently create and customize skill motions by recording their own movements and having the system automatically process them into game character animations. This self-service approach eliminates the need for professional animators while enabling full customization, resolving the contradiction between development efficiency and user adaptability.
2Adaptability or versatility
If skill motions are customized for each user, then user personality reflection is improved, but system complexity increases
Solution Approach 1:
The system replaces complex manual animation creation processes with automated image processing and motion recognition algorithms. By substituting the mechanical process of frame-by-frame animation with automated computer vision technology, the system enables user customization without proportionally increasing system complexity. The automated skeleton extraction and motion mapping handle the complexity internally while presenting a simple user interface.
Solution Approach 2:
The system introduces an intermediary processing layer that automatically converts user-recorded images/videos into game character animations. This intermediary layer handles the complex transformations between different coordinate systems and motion representations, shielding users from complexity while enabling personalized motion customization.
3Productivity
If automated skeleton extraction is implemented, then motion data processing efficiency is improved, but measurement precision requirements increase
Solution Approach 1:
The system performs preliminary actions by pre-processing images to enhance features before skeleton extraction. This includes image normalization, noise reduction, and feature enhancement that prepare the data for more accurate and efficient skeleton detection. By performing these preliminary actions, the system reduces the precision requirements during the actual extraction phase while maintaining overall accuracy.
Solution Approach 2:
The system implements feedback mechanisms where the skeleton extraction results are continuously refined based on detected errors and inconsistencies. The system adjusts its extraction algorithms based on feedback from multiple detection passes, improving both precision and efficiency through iterative optimization rather than requiring perfect precision in a single pass.
Data Source
AI summary
A method for providing a game service and a server for performing the same are disclosed. A method by which a server provides a game service can comprise the steps of: receiving image data including motion data from a user terminal; generating skill motion sequence data of a game character corresponding to the motion data; and adjusting a skill motion of the game character on the basis of the generated skill motion sequence data.