Emotion Augmented Avatar Animation via Layered Pre-rendering
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Solution Overview
Problem
Existing avatar systems are often static, computation-intensive, and not suitable for mobile devices, lacking the ability to effectively convey user emotions in electronic communications.
Innovation Solution
An avatar system with an animation augmentation engine that analyzes facial data to determine user emotions and supplements avatar animations with emotion-based augmentations, using a facial expression and head pose tracker, animation augmentation engine, and avatar animation engine to provide dynamic and emotion-driven animations on a wide range of devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing avatar systems use facial expression tracking with high-performance processors, then emotion recognition accuracy is improved, but device complexity and computational requirements increase making it unsuitable for mobile devices
Solution Approach 1:
The system segments the avatar animation into multiple layers: a base layer containing the avatar model and a separate animation layer containing pre-rendered emotion-based animations. This segmentation allows emotion tracking to trigger specific animation layers without requiring real-time complex computations, reducing device complexity while maintaining accuracy.
Solution Approach 2:
The system pre-renders emotion-based animation sequences offline and stores them in the animation layer. When emotion recognition detects a specific emotional state, the corresponding pre-rendered animation is activated immediately without requiring real-time complex computation, thus maintaining high accuracy while reducing computational requirements on mobile devices.
2Adaptability or versatility
If avatar systems use static images or simple GIF animations, then device compatibility is improved, but user engagement and emotion expression capability deteriorate
Solution Approach 1:
The system implements dynamic avatar animation by separating the static base layer from the dynamic animation layer. The animation layer contains multiple emotion-specific animation sequences that are dynamically activated based on detected emotional states, enabling rich emotion expression while maintaining compatibility across different devices through the layered architecture.
Solution Approach 2:
The system uses pre-rendered animation copies stored in the animation layer that replicate complex emotion expressions. These copied animation sequences can be played back without requiring heavy computational resources, thus maintaining device compatibility while providing engaging emotion-driven animations.
3Ease of operation
If real-time emotion-driven animation is implemented, then user engagement is improved, but computational load increases making it difficult to run on mobile devices
Solution Approach 1:
Complex animation computations are performed in advance and stored as pre-rendered sequences in the animation layer. During runtime, the system only needs to detect emotions and activate corresponding pre-computed animations, dramatically reducing real-time computational load and energy consumption on mobile devices while maintaining high user engagement through responsive emotion-driven animations.
Data Source
AI summary
Apparatuses, methods and storage medium associated with emotion augmented animation of avatars are disclosed herein. In embodiments, an apparatus may comprise an animation augmentation engine to receive facial data of a user, analyze the facial data to determine an emotion state of the user, and drive additional animation that supplements animation of the avatar based at least in part on a result of the determination of the emotion state of the user. Other embodiments may be described and/or claimed.