Digital Human Lighting Assembly for Contextual Interaction
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Solution Overview
Problem
Current technologies lack the capability to effectively develop and render interactive digital humans with human-like attributes, such as natural language processing and contextual responses, for real-time user interactions.
Innovation Solution
A digital human development method and system that allows users to select a digital human, specify dialogues and behaviors, and generate scene data by merging behaviors with dialogue on a common timeline, enabling real-time contextual responses and human-like interactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If digital humans are designed with complex AI capabilities for natural language processing and contextual responses, then the quality of human-like interactions is improved, but the device complexity and development difficulty increase
Solution Approach 1:
The system divides the digital human creation process into separate modules: dialogue tracking, behavior animation, and scene composition. Each module handles specific aspects independently, allowing complex interactions to be built from manageable components without overwhelming system complexity
Solution Approach 2:
The digital human platform integrates multiple functions into a single system including NLP processing, behavior animation, dialogue management, and visual rendering. This multi-functional approach consolidates complexity into one unified system rather than requiring separate systems for each function
2Productivity
If real-time interactive responses are implemented, then user engagement is improved, but processing time and computational requirements increase
Solution Approach 1:
The system pre-processes and prepares dialogue responses and behavioral animations before user interaction occurs. Dialogue options and corresponding behaviors are pre-computed and stored, allowing rapid retrieval and execution during real-time interaction without requiring complex computations at the moment of interaction
Solution Approach 2:
The system dynamically adjusts the level of interactivity and processing intensity based on the current interaction context. For simple interactions, minimal processing is applied while maintaining responsiveness. For complex scenarios, the system can increase processing depth without compromising real-time performance through adaptive resource allocation
3Shape
If detailed behavior animations and facial expressions are added to digital humans, then human-like appearance is improved, but the difficulty of detecting and measuring appropriate responses increases
Solution Approach 1:
The system incorporates feedback mechanisms that continuously monitor user responses and adjust digital human behaviors accordingly. Facial expressions and body language are synchronized with dialogue content based on real-time feedback about user engagement and interaction context, ensuring appropriate behavior without requiring complex detection algorithms
Solution Approach 2:
The system controls behavioral parameters such as facial expression intensity, body movement speed, and gesture duration through adjustable parameters rather than complex real-time detection. This allows precise control of human-like appearance through parameter modulation while avoiding the measurement difficulties associated with detecting subtle human behaviors
Data Source
AI summary
Communications pertaining to a digital human can include communicating via a lighting system based on determining an aspect of a user based on one or more sensor-generated signals. A communicative lighting sequence can be determined based on the user attribute. The lighting sequence can correspond to a condition of a digital human and can be configured to communicate to the user the condition of the digital human. The light sequence can be generated with an LED array mounted on a digital human display assembly.