Virtual Avatars for Immersive Human Motion Analysis
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Solution Overview
Problem
Current methods for analyzing human motion data within spaces lack the ability to provide detailed insights into specific behaviors and interactions, offering only a high-level overview of human movement without context regarding the space or interactions with objects and people.
Innovation Solution
A computer-implemented method that generates virtual avatars based on motion data, positioning them within an extended reality environment to visualize human movements in context, allowing for detailed analysis of behaviors and interactions by displaying these avatars in a 3D space.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If data visualizations are displayed within AR or VR environments, then the context of the space is improved, but the ability to analyze specific behaviors and interactions deteriorates
Solution Approach 1:
The system segments the visualization into multiple components: virtual avatars representing individuals, spatial environment representations, and interaction indicators. Each component provides different levels of information, allowing users to analyze both contextual space usage and specific behavioral details simultaneously within the AR/VR environment.
Solution Approach 2:
Virtual avatars serve as intermediaries between the raw motion data and the AR/VR visualization. These avatars encode detailed behavioral information (postures, gestures, interactions) while representing individuals within the spatial context, bridging the gap between contextual visualization and detailed behavior analysis.
2Productivity
If traditional data visualizations are used, then the overview of human movement is provided, but the detail of space context and interactions is lost
Solution Approach 1:
The system transitions from traditional 2D data visualizations to immersive 3D AR/VR environments. This dimensional change allows simultaneous representation of spatial context, individual movements, and interactions in a way that preserves detail while maintaining analytical efficiency. Users can navigate and explore the data from multiple perspectives.
Solution Approach 2:
The system creates virtual copies (avatars) of real people based on captured motion data. These digital twins preserve detailed behavioral information including postures, gestures, and interaction patterns, allowing analysis of specific behaviors without requiring observers to be physically present in the space.
3Measurement precision
If virtual avatars are generated and displayed in ER scene, then the detail of behavior analysis is improved, but the complexity of the system increases
Solution Approach 1:
The virtual avatar system serves multiple functions simultaneously: it represents individual identity, encodes spatial position, captures body posture and gestures, and indicates interactions with objects and other people. This multi-functionality reduces the need for separate visualization systems for each type of information, managing complexity through consolidation.
Solution Approach 2:
The system changes the parameter representation from raw coordinate data to semantic avatar attributes. Motion data parameters (x, y, z coordinates, joint angles) are transformed into meaningful avatar properties (position, posture, gestures, interactions), making the data more interpretable while managing computational complexity through standardized parameter mappings.
Data Source
AI summary
One embodiment of a computer-implemented method for analyzing human motion data includes receiving a set of motion data that indicates one or more movements of a first person within a real-world environment; generating a virtual avatar corresponding to the first person based on the set of motion data; determining a position of the virtual avatar within an extended reality (ER) scene based on the one or more movements; and displaying the virtual avatar in the ER scene according to the determined position.