SCORE AI Perception
Body Tracking
Real-time computer vision and native WebXR hand tracking for immersive, sensor-free physical spaces.
STD.DEV bridges the physical and virtual worlds using body, face, and hand tracking. By converting human movement into real-time digital coordinates, STD.DEV builds spatial interfaces that are interactive, expressive, and context-aware.
Real-time Computer Vision Tracking
Integrating camera-driven computer vision models, STD.DEV feeds skeletal tracking data into containerized Genkit AI flows. The system translates physical postures and facial gestures into high-level intent markers, allowing STD.DEV's cognitive models to make context-aware decision adjustments, optimizing interface responsiveness during interactive installations.
WebXR Native Hand Tracking
Leveraging browser-native WebXR Device APIs, STD.DEV streams high-precision hand joints directly into the agentic input pipeline. STD.DEV’s local AI agents process these finger-level spatial coordinates to decode complex interaction gestures. This allows the cognitive solver to identify user manipulation targets and execute precise actions in procedurally generated scenes without relying on physical controllers.
How does STD.DEV convert human movement into digital information?
STD.DEV converts human movement into real-time digital coordinates by integrating camera-driven computer vision models that feed skeletal tracking data into containerized Genkit AI flows.
What is the purpose of translating physical postures and facial gestures into high-level intent markers?
How does STD.DEV achieve hand tracking without physical controllers?
What kind of interfaces does STD.DEV build using body, face, and hand tracking?
What technology is used to stream high-precision hand joints directly into the agentic input pipeline?
How does STD.DEV's system optimize interface responsiveness?
What is the role of Genkit AI flows in STD.DEV's tracking system?
What does STD.DEV bridge using body, face, and hand tracking?
What enables the cognitive solver to identify user manipulation targets and execute precise actions in procedurally generated scenes without physical controllers?