Basic Emotion Recognition Model

Integrate emotional insights into your application.

Basic Emotion Recognition Model

From Visual Raw Data to Structured Emotional Insights.

A computer vision model designed to detect seven basic human emotions.

· Input: Stills or RTSP streams; supports up to 4K resolution; handles low-light and off-axis angles (up to 45°).

· Output: Real-time JSON response including emotion labels (Happiness, Sadness, Anger, Fear, Surprise, Disgust, and Neutral.), confidence scores, and facial bounding boxes.

Edge

Why Top-Tier Enterprises Choose MinsightAI.

· Unmatched Robustness: Unlike standard models that fail in the wild, our model is trained on 45,000+ labeled entries per class, ensuring stability in both close-up and surveillance-angle, as well as across differnet ethnic groups.

· High-Velocity Inference: Engineered for high-concurrency. Experience a 3ms latency (GPU-based), allowing for seamless real-time monitoring across hundreds of simultaneous feeds.

· Superior Recall for Risk: Optimized specifically for “Negative Emotion Detection” (Anger, Fear, Sadness), outperforming general-purpose models.

Benchmarks

Scenario	Distance/Setup	Accuracy
Close-Up (Interviews, Checkpoints…)	< 1.5m, Eye-level	96%
Wide-Angle (Public Safety, Schools…)	2-3m Height, Surveillance Angle	90%

Flexibility

Integrate Anywhere, Scale Everywhere.

· Cloud API: Rapid integration via RESTful API for web and mobile applications.

· Private Cloud: Deploy on your own infrastructure (AWS, Azure, GCP) for total data control.

· On-Premise / Edge: Optimized for NVIDIA Triton and local servers in air-gapped or low-bandwidth environments.

Ready to Auto-Read Abnormal Body Movements?

Start building with our Basic Emotion Recognition Model API today.