Handsoutput

Handsoutput is a term used in human-computer interaction and gesture-recognition contexts to describe the structured data produced by hand-tracking systems. A handsoutput typically captures the spatial, temporal, and semantic information derived from one or more hands, such as position, orientation, joint angles, velocity, and detected gestures. It serves as an intermediate representation that applications use to interpret user intent and translate it into commands or feedback.

A typical handsoutput record may include: timestamp; hand_id or side (left or right); palm_position (x, y, z) in a defined coordinate system; palm_orientation (quaternion or Euler angles); finger_joints (array of joints with coordinates or angles); gesture label; confidence scores; velocity and acceleration; tracking_status; and optional raw sensor data.

Data is commonly serialized as JSON, though binary formats or XML may be used in low-latency pipelines. Outputs can be produced as streams or in batched form, and may be delivered through event-driven or polling interfaces. Applications that consume handsoutput range from virtual reality and augmented reality input to sign-language recognition, teleoperation of robots, and touchless user interfaces.

There is no universal standard named handsoutput, but many toolkits and SDKs define similar structures and field conventions. Adoption often depends on the software stack and hardware sensors (depth cameras, infrared sensors, or data gloves). Challenges in producing reliable handsoutput include occlusion, latency, noise, calibration drift, and privacy considerations.

See also: hand tracking, gesture recognition, motion capture, virtual reality input.