This page describes the structural model and configurable components of FanRows.
FanRows is implemented as a modular framework for embodied audio interaction. The architecture separates motion analysis, state regulation, audio control, and configuration in order to enable reproducible experimentation with continuous body–sound coupling.
FanRows consists of four primary layers:
Each layer can be modified independently while preserving the overall interaction model.
Webcam Pose Tracking
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Feature Extraction (angles, velocity, stability, persistence)
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Regulation Layer (thresholds, hold-times, state transitions)
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Audio Engine (layered loops, gain-based activation, FX)
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Config (JSON Sessions/Scenes) + Studio (calibration UI)
Input is derived from webcam-based pose tracking.
The system continuously extracts features such as:
These features define the regulatory input space. No symbolic commands or discrete events are generated at this stage.
FanRows operates through gradual state transitions rather than discrete triggering.
Loop activation is achieved via:
State changes emerge from sustained spatial configurations rather than single gestures. This structure allows reproducible regulatory contexts without relying on timeline-based sequencing.
The audio engine manages layered sound states.
Key characteristics:
All audio layers are controlled through regulation curves rather than event calls.
A session represents a concrete interaction instance under a defined configuration.

Sessions serve as structured observation environments in which:
can be examined over time.
A session is not a performance or composition. It is a defined system state under observation.
Scenes define bounded regulatory spaces within a session.

A scene specifies:
Scene transitions are triggered by sustained body configurations, not by discrete events. Scenes structure the interaction space without introducing timeline-based progression.
Studio provides calibration, inspection, and structural refinement tools. It is designed to stabilize experimental conditions and expose regulatory parameters — rather than to function as a traditional music production interface. Studio allows controlled adjustment of thresholds, persistence logic, parameter mappings, and scene transitions.
The main Studio interface exposes scene configuration, loop definitions, and regulatory parameter mappings. It provides structured access to motion–sound relationships while preserving the modular system architecture.

The baseline defines the default parameter state of the audio system before dynamic modulation is applied. It establishes stable conditions for scene-level and loop-level processing.
The global baseline controls scene-wide audio parameters such as filter states, spatial characteristics, and global modulation settings. These parameters affect all active layers within the current scene.

Per-loop baseline settings define default parameter states for individual sound layers. This allows differentiated tonal or spatial conditions within the same scene.

Effect mappings define how continuous motion features influence audio parameters in real time. Mappings operate as modulation layers above the established baseline.
The Cue Engine introduces controlled temporal variation within a scene. It modulates selected parameters over time using probabilistic activation and gradual parameter curves, without interrupting playback.

Velocity mappings translate movement intensity into continuous parameter modulation. This enables dynamic responsiveness based on motion speed rather than discrete triggers.

Pose mappings associate sustained spatial configurations with parameter changes or state transitions. Activation depends on temporal persistence rather than instantaneous detection.

Limb angle mappings allow specific joint angle relationships to regulate audio parameters. This enables fine-grained control based on spatial articulation rather than gross movement.

This mapping layer defines which poses or motion states regulate specific loop activations. Loop behavior is governed through continuous gain modulation rather than start–stop logic.

The confidence view displays detection stability and threshold evaluation in real time. It provides diagnostic insight into how reliably the system interprets motion and posture states during interaction.

FanRows integrates:
The architecture enables controlled modification of regulatory parameters while maintaining a stable interaction model.
FanRows — Continuous Embodied Audio Interaction
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