PAD Emotion Recognition Model

Integrate emotional insights into your application.

PAD Emotion Recognition Model

From Categorical Labels to Multidimensional Affective Mapping.
Moving beyond simple “Happiness” or “Sadness” labels, our PAD model quantifies emotions within a three-dimensional psychological space: Pleasure (positivity), Arousal (activation), and Dominance (control). This allows for the mathematical tracking of emotional trajectories and intensities.

· Input: Stills or video segments (10-15s recommended for offline analysis); supports 1080p+ resolution; optimized for front-facing interactions.

· Output: Real-time JSON response providing continuous P, A, and D values, mapped to 8+ complex psychological states (e.g., Hostility, Tension, Depression, Relaxation).

Edge

Why Top-Tier Enterprises Choose MinsightAI.

· Granular Intensity Detection: While competitors only identify “Anger”, our model distinguishes between mild annoyance and explosive rage by measuring the Arousal and Dominance levels—critical for high-stakes risk assessment.

· Expert-level Precision: Grounded in the Mehrabian & Russell (1974) framework and trained on 38,000+ expert-labeled samples, achieving a human-machine consistency correlation of up to 91.

· Advanced Psychological Semantics: Enables the detection of complex “subtle” states like Contempt, Dependence, and Boredom, providing actionable insights for interrogations, mental health screenings, and UX research.

Benchmarks

Scenario	Detection Target	Accuracy / Correlation
Real-Time Analysis	Pleasure (P) Correlation	0.91
Real-Time Analysis	Arousal (A) Correlation	0.83
High-Risk States	Hostility Detection	93%
Psychological Stress	Tension Detection	88%

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 Quantify Human Emotion?

Start building with our PAD Emotion Recognition Model API today.