Getting Started
Technical Docs
AURORA⁺ Documentation
Learn how to use AURORA⁺ to detect emotions and track attention in real-time.
Getting Started
AURORA⁺ is a powerful emotion recognition and attention tracking system that uses cutting-edge AI to analyze facial expressions and voice patterns in real-time.
Technology Overview
AURORA⁺ combines computer vision, machine learning, and real-time processing to deliver accurate emotion recognition and attention tracking. Here's how our technology works:
Neural Networks
Our system uses deep convolutional neural networks trained on diverse datasets to recognize subtle facial expressions and map them to emotional states with high accuracy.
Computer Vision
Advanced facial landmark detection identifies 68 key points on the face, tracking micro-expressions and subtle changes that indicate different emotional states.
Real-time Processing
Optimized algorithms process video frames in milliseconds, providing immediate feedback on emotions and attention levels without noticeable latency.
How Emotion Recognition Works
- Face Detection: The system first locates faces in the video frame using efficient detection algorithms.
- Facial Landmark Extraction: Once a face is detected, the system identifies key facial landmarks such as eyes, eyebrows, nose, mouth, and jaw.
- Feature Analysis: The spatial relationships between these landmarks are analyzed to identify facial expressions.
- Emotion Classification: A neural network classifies these expressions into emotional states like happiness, sadness, anger, surprise, etc.
- Confidence Scoring: Each emotion detection is accompanied by a confidence score indicating the reliability of the classification.
Key Features
AURORA⁺ offers a comprehensive suite of features designed to provide deep insights into emotional states and attention levels:
Emotion Detection
Recognizes seven primary emotions: happiness, sadness, anger, surprise, fear, disgust, and neutral states. The system can detect subtle emotional changes and transitions between emotional states.
Happy
Sad
Angry
Surprised
Attention Tracking
Monitors eye gaze direction, head position, and blinking patterns to determine focus levels and attention span. Provides real-time feedback on distraction events and focus duration.
Real-time Analysis
All processing happens in real-time with minimal latency, allowing for immediate feedback and responsive applications. The system can process up to 30 frames per second on standard hardware.