elara-visual
Visual processing engine for the ELARA Protocol - featuring keyframe encoding, predictive algorithms, and graceful degradation for real-time video communication.
Features
- Keyframe Encoding: Efficient video state representation
- Predictive Algorithms: Temporal and spatial prediction
- Graceful Degradation: Quality reduction under network stress
- Face State Processing: Emotion and expression tracking
- Pose Prediction: Body movement prediction and interpolation
- Scene Reduction: Automatic detail level adjustment
Quick Start
use ;
use StateId;
// Create visual encoder
let mut encoder = new;
// Create predictor
let mut predictor = new;
// Encode visual frame
let visual_state = encoder.encode_frame?;
// Predict next state
let predicted = predictor.predict?;
Visual State Model
Keyframe Structure
Degradation Levels
Full Quality → Reduced Quality → Symbolic → Presence Only
↓ ↓ ↓ ↓
Complete Essential Minimal Existence
Detail Features Info Proof
Encoding Process
// High quality encoding
let high_quality = encoder.encode_with_quality?;
// Adaptive encoding based on network
let adaptive = encoder.encode_adaptive?;
// Symbolic encoding for minimal bandwidth
let symbolic = encoder.encode_symbolic?;
Prediction Algorithms
Face Prediction
- Emotion vector interpolation
- Viseme generation from phonemes
- Eye movement prediction
Pose Prediction
- Joint position interpolation
- Movement trajectory prediction
- Constraint-based correction
Scene Prediction
- Background stability detection
- Lighting change prediction
- Object persistence tracking
Network Adaptation
// Update based on network conditions
encoder.adapt_to_network;
// Manual quality setting
encoder.set_quality_level;
// Automatic degradation
encoder.enable_auto_degradation;
License
Licensed under either of:
- Apache License, Version 2.0 (LICENSE-APACHE or http://www.apache.org/licenses/LICENSE-2.0)
- MIT license (LICENSE-MIT or http://opensource.org/licenses/MIT)
at your option.
Contribution
Unless you explicitly state otherwise, any contribution intentionally submitted for inclusion in the work by you, as defined in the Apache-2.0 license, shall be dual licensed as above, without any additional terms or conditions.