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Computer Vision & Deep LearningSystem ID: EVR-VISION-08•3 min read

Micro-Expression & Facial Emotion Classifier

Deep learning facial expression recognizer trained to identify micro-expressions, attention spans, and moods in real time.

Primary Impact:Real-Time Inference
Core Stack:JavaScriptTensorFlow.jsCNNDeep Learning
Micro-Expression & Facial Emotion Classifier
!The Challenge

Operational Friction & Bottlenecks

Measuring user engagement and affective responses in web applications or digital interviews traditionally requires intrusive equipment.

✓The Evaroid.AI Solution

Engineered AI Architecture

A lightweight CNN model running on-device inside the browser using TensorFlow.js that detects 7 core human emotion expressions in real time without sending video frames to servers.

System Architecture

Technical Execution & Pipeline Flow

EVR-VISION-08 FLOW
1
Webcam capture via HTML5 MediaStream API
2
Client-side face bounding box localization and landmark alignment
3
Quantized convolutional neural network evaluating pixel intensity tensors
4
7-class softmax emotion probability distribution calculation
5
Real-time visual telemetry and engagement trend computation

Measurable Results & Business Impact

60 FPS
In-Browser Frame Rate
0 KB
Video Data Sent to Servers (Private)
7
Distinct Affective States Classified

Key Capabilities & Features

100% client-side privacy-first inference with zero server uploads
Lightweight model weight footprint (<12MB)
Real-time 60 FPS performance on standard laptops and smartphones
Detects subtle micro-expressions and attention shifts

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