XR Avatar Authoring via Segmented Cloud Processing
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Solution Overview
Problem
Current technologies face challenges in enhancing the expressiveness and detail of avatars in Extended Reality (XR) and Virtual Reality (VR) while managing computational resources and security, particularly in mobile devices, and offer limited customization and security features.
Innovation Solution
A method for authoring and managing avatars that includes capturing and integrating visual, audio, and time-based data to generate and improve avatar systems, using unique identification strings for authentication and economic models, and employing machine learning for predictive analytics and security measures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If avatar detail and expressiveness are improved, then avatar quality is enhanced, but computational requirements exceed mobile device capabilities
Solution Approach 1:
The system segments avatar processing into multiple components: base avatar generation, detail enhancement layers, and stylistic modifications. Each component can be independently processed and rendered, allowing mobile devices to handle only the essential rendering while more complex processing occurs in the cloud or during idle time.
Solution Approach 2:
Avatar details and high-fidelity data are pre-computed and stored in the cloud before the user needs them. When a user wants to view or edit their avatar, the mobile device retrieves pre-processed data rather than performing intensive real-time computation, significantly reducing local computational requirements.
2Adaptability or versatility
If avatar customization options are increased, then user expression capability is improved, but system complexity increases
Solution Approach 1:
The system provides a universal set of avatar customization parameters that can be applied across multiple platforms and use cases. A single avatar data structure supports various customization needs (appearance, style, behavior) through a unified interface, reducing the need for separate complex systems for each customization type.
Solution Approach 2:
The patent introduces an intermediary layer between the user interface and the avatar rendering system. This intermediary handles the complexity of customization options by providing standardized parameters and data structures that simplify communication between the mobile device, cloud services, and various rendering engines.
3Reliability
If avatar data security is strengthened, then identity protection is improved, but data access and processing become more difficult
Solution Approach 1:
Security credentials and authentication data are pre-established and stored securely in the cloud before any avatar operations occur. This allows the system to verify identities and authorize access to avatar data without requiring complex real-time security checks on the mobile device, maintaining both security and ease of operation.
Solution Approach 2:
The patent introduces a security intermediary layer that manages authentication and authorization for avatar data. This intermediary handles cryptographic operations and access control in the cloud, allowing mobile devices to access avatar data through simple authenticated requests without implementing complex security protocols locally.
Data Source
AI summary
Systems and methods for digital avatars, specifically for fashion and consumer goods, are provided. This system is useful with an identified avatar, environment, and objects that a user may author, edit, and place. A user may deploy an avatar that resembles themselves via augmented reality, virtual reality, and other types of media. These systems include a user interface, administrative interface, economic systems and means of managing assets and protecting users' data. The systems incorporate mechanisms of controlling the avatar, means of integrating physical sensor data that interoperates with the virtual, and means of predicting related trends, choices, and behavior. Various features are employed for increased efficiency, accuracy, and believability. These features include machine learning to produce avatar features, AR map directions to interact with avatars, computer vision to enable the real-time translation of physical to virtual and social structures to enable groups of people to create and license digital assets.