Virtual Object Motion Modeling for Realistic Game Trajectories
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Solution Overview
Problem
Existing video games struggle with the time-consuming and costly process of manually orchestrating realistic movements of virtual objects, especially when dealing with a large number of objects, as the depiction often lacks realism and requires significant human intervention.
Innovation Solution
Implement motion models trained on video game clips and other video training clips to determine the trajectory and movement of virtual objects based on parameters such as weight, fragility, and deformation, allowing for automatic generation of realistic virtual motion without extensive human coordination.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If motion models trained on video clips are implemented to automatically determine virtual object movement, then the time and cost required to create realistic virtual motion is significantly reduced, but the complexity of the system increases due to the need for machine learning models and training data processing
Solution Approach 1:
The patent replaces the manual mechanical process of orchestrating virtual object motion with an automated machine learning-based system. Motion models trained on video clips automatically determine trajectories and movements, substituting human manual configuration with AI-driven automated generation, thereby significantly improving productivity despite increased system complexity
Solution Approach 2:
The motion models are trained in advance on extensive video clip data to learn realistic movement patterns. This preliminary training action enables the system to automatically generate realistic virtual motion without requiring manual orchestration during actual game development, resolving the contradiction between productivity improvement and system complexity
2Reliability
If manual orchestration is used to depict realistic virtual object movement, then the realism of the depiction can be maintained, but the process becomes time-consuming and expensive when dealing with a large number of virtual objects
Solution Approach 1:
The patent substitutes manual orchestration with automated motion models that learn realistic movement patterns from trained video data. This substitution maintains realism through AI-learned patterns while dramatically reducing the time required to create virtual motion for large numbers of objects
Solution Approach 2:
The motion models automatically generate realistic virtual motion trajectories without requiring human intervention for each object. The system serves itself by using trained AI models to determine movements, maintaining realism while eliminating the time-consuming manual orchestration process
Data Source
AI summary
A video game system and method analyze virtual contact between an avatar and a virtual object within a video game. The point of contact of the virtual contact on the virtual object and/or the intensity of contact of the virtual contact may then be used to determine a subsequent virtual action to be performed within the video game. The virtual action, with any virtual movement thereof, may be carried out in a realistic manner within the video game by determining a virtual trajectory of the motion. The virtual trajectory may be determined using a motion model. The motion model may provide the virtual trajectory of the virtual object based at least in part on one or more parameters of the virtual object, such as a weight parameter. The motion model may be trained using training video clips with realistic motion of virtual objects.