Group emotion data
robots can actually
learn from.
Existing emotion datasets fail
under real-world conditions.
Single-actor footage ignores how emotions shift in group dynamics — your robot reads a crowd of two as a crowd of one.
Labels stop at facial action codes. There is no semantic layer connecting expression to conversational intent or social context.
Motions lack physics constraints — models trained on bad kinematic data hallucinate impossible body positions at inference time.
Three layers of truth,
not one layer of labels.
Sentic captures real group interactions simultaneously across face, body, and proxemics — then enriches every frame with a semantic intent layer and validates the full sequence against physics engine constraints before any data leaves our pipeline.
Group capture → Semantic enrichment → Physics validation
Three systems. One dataset you can trust.
Simultaneous multi-person emotion capture at scene level.
Existing datasets isolate individuals. Sentic captures every person in a scene simultaneously — tracking face landmarks, full-body joint kinematics, gaze vectors, and proxemic distances between all participants in real time.
Group dynamics change everything. A raised eyebrow means one thing in isolation; it means something entirely different when three people are watching. Our data captures that difference.
MediaPipe + custom AU classifier trained on in-house annotator consensus.
Full-body pose in 3D world coordinates, not 2D projection artifacts.
Crowd-level social scenes captured with per-person identity tracking.
High-speed capture preserves micro-expression onset and offset timing.
Every frame knows what the emotion means, not just what it looks like.
FACS codes and AU labels tell you a muscle moved. They cannot tell you whether that micro-expression signals amusement, social compliance, or suppressed anxiety in a given group context.
Sentic appends a semantic intent vector to every annotation — linking expression data to conversational and social function so your model learns the why alongside the what.
Biomechanically valid or it does not ship.
Every motion sequence in the Sentic pipeline passes through a physics engine validation step. Joint angles are checked against anatomical limits. Velocity and acceleration profiles are verified for biomechanical plausibility. Sequences that fail are flagged and re-captured, not patched.
The result: models trained on Sentic data do not hallucinate impossible poses at inference time — a critical requirement for any robot operating in proximity to humans.
Elbow, shoulder, spine, and hip angles verified against published human ROM limits across 7 joint types.
Frame-to-frame kinematic derivatives checked for biologically plausible movement speeds — flags capture artifacts and jitter.
Sequences failing validation are discarded and re-recorded. We do not interpolate or synthetically patch failed frames.
Built for teams that cannot afford to train on noise.
Give your robot the social awareness to operate near humans safely.
Humanoid robots entering real workplaces and homes need to read group emotional states — not just individual faces. Sentic datasets train the models that power socially-aware navigation, interaction timing, and proximity management.
NPCs that react to the whole room, not just the closest player.
Game AI characters trained on Sentic data understand crowd emotional dynamics — how tension builds in a group, how laughter propagates, when a crowd turns. The result is believable social AI that players feel rather than analyze.
A foundation dataset your emotion recognition models can grow from.
API companies building emotion recognition at scale need diverse, densely-annotated training data with strong social-context coverage. Sentic licenses full annotation schemas and delivery pipelines for direct integration into your training infrastructure.
What you receive with a Sentic dataset license
Your AI models deserve data that holds up in the real world.
Sentic works with robotics teams, game AI studios, and affective computing companies on a direct license basis. Tell us about your training data requirements and we will respond within one business day.
NDA-protected previews available. Enterprise SLAs on request.
A Sentic data engineer reviews your use case and sends a scoped proposal.
Review 500 annotated frames with full schema documentation before any commitment.
License existing data or commission a custom capture batch tuned to your model requirements.