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 elara_visual::{VisualEncoder, VisualPredictor, VisualState};
use elara_core::StateId;

// Create visual encoder
let mut encoder = VisualEncoder::new(config);

// Create predictor
let mut predictor = VisualPredictor::new(prediction_config);

// Encode visual frame
let visual_state = encoder.encode_frame(frame_data)?;

// Predict next state
let predicted = predictor.predict(&current_state, &history)?;

Visual State Model

Keyframe Structure

pub struct VisualState {
    pub face: FaceState,        // Facial expressions and emotions
    pub pose: PoseState,        // Body position and movement
    pub scene: SceneState,      // Environmental context
    pub timestamp: StateTime,   // Temporal reference
}

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(frame, Quality::High)?;

// Adaptive encoding based on network
let adaptive = encoder.encode_adaptive(frame, network_quality)?;

// Symbolic encoding for minimal bandwidth
let symbolic = encoder.encode_symbolic(frame)?;

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(network_quality);

// Manual quality setting
encoder.set_quality_level(QualityLevel::Medium);

// Automatic degradation
encoder.enable_auto_degradation(true);

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.