Motion Graph Animation for Responsive Multiplayer Character Movement
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Solution Overview
Problem
Current methods for animating characters in video games, such as animation state machines (ASMs) and motion graphs, struggle with realism, scalability, responsiveness, and data efficiency, failing to produce lifelike character movements, especially in complex interactions and tight spaces.
Innovation Solution
A graph structure is generated from motion capture data by identifying dominant poses, grouping them into master nodes, calculating transitions, and applying inverse blend shapes and normal maps to synthesize character motion, enhancing realism and responsiveness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If animation state machines (ASM) are used to animate characters, then character motion can be controlled through predefined clips, but the realism of motion suffers because animators can only conceive of a limited number of clips while achieving realism requires a far greater number
Solution Approach 1:
The patent segments character motion into discrete poses captured from motion capture data, organizing them into a graph structure where nodes represent poses and edges represent transitions. This segmentation allows the system to use a limited set of captured poses rather than requiring animators to create numerous clips, while still achieving realistic motion through proper pose selection and blending.
Solution Approach 2:
The patent uses motion capture data to copy realistic human motion directly into the game character, rather than relying on animator-created clips. By capturing and reproducing actual human movement data, the system achieves high realism without requiring animators to manually create a large library of animation clips.
2Adaptability or versatility
If animation state machines (ASM) are used to handle new interactions, then character motion can be extended to new scenarios, but the system does not scale well since any new interaction requires a number of entry and exit points to connect with the data, the creation of which scales geometrically
Solution Approach 1:
The patent creates a universal graph structure that can handle multiple types of interactions and scenarios through a single unified system. The graph nodes and edges provide a flexible framework that can represent various interactions without requiring separate animation state machines for each scenario, allowing the same structure to serve multiple functions.
Solution Approach 2:
The patent implements a dynamic motion graph where transitions between poses are determined by real-time game state and character constraints rather than predefined state machines. This dynamic approach allows the system to adapt to new interactions by evaluating pose similarity and transition costs at runtime, rather than requiring pre-configured entry and exit points for every possible interaction.
3Duration of action of stationary object
If animation clips are continuously played from a core library, then character motion can be maintained, but the same poses are continuously achieved introducing a tiling effect over time that is similar to texture tiling over space
Solution Approach 1:
The patent uses feedback mechanisms to monitor the character's current pose and the animation timeline, dynamically selecting and blending poses from the motion capture library to avoid repetition. The system evaluates pose similarity and transition costs to ensure that the same poses are not continuously replayed, thereby eliminating the tiling effect while maintaining continuous animation.
4Speed
If motion matching continuously searches the entire animation dataset for the next frame, then responsiveness to changing animation goals is improved, but it can be hard to predict and control which animation data will be selected at any given time
Solution Approach 1:
The patent pre-calculates and stores pose similarity metrics and transition costs for all pairs of poses in the motion capture dataset during an offline preprocessing stage. This preliminary action creates a structured graph representation that enables fast runtime query and prediction of which poses will be selected, while maintaining responsiveness by avoiding continuous full-dataset searches.
5Manufacturing precision
If the animation database grows to improve one area of motion, then character motion quality is enhanced, but newly introduced or modified animation data may negatively affect others, leading to a reluctance to make changes
Solution Approach 1:
The patent segments the animation database into discrete poses represented as graph nodes, with pre-calculated similarity metrics and transition costs between pairs of poses. This segmentation allows individual poses to be added, removed, or modified independently without affecting the entire animation system, as the graph structure and pre-calculated metrics isolate changes to local connections rather than requiring system-wide reconfiguration.
Data Source
AI summary
Systems and methods for constructing an offline graph structure configured to enable controlled character motion synthesis in a multi-player online gaming include a graph structure that has a plurality of master nodes and edges such that each master node is representative of a set of similar dominant poses and edges are representative of plausible transitions between these dominant poses. Motion is generated at runtime by navigating through the graph structure and applying dominant poses from the plurality of master nodes. Since, an online game describes a desired motion of a character using a plurality of control parameters therefore, transitions that match the plurality of control parameters most closely are selected from the graph structure.