Trace
Amounts

A secret data collection system installed at a house party without the guests' knowledge. A camera above a black table tracked condensation rings and cup stains throughout the night — translating unconscious social behavior into a live projection and a printed artifact. The system was designed to be visible but unexplained.

Detected Parameters

Position X and Y coordinate of each stain on the surface

Completeness How much of the ring's circumference is present

Edge Roughness Irregularity of the ring boundary

Darkness Contrast of the stain against the table surface

Area Physical size of the stain

Overview

Python uses Hough circle detection to identify cup stains and condensation rings on the table surface in real time. Each detected ring is evaluated across five parameters and dispatched as an individual data packet to two simultaneous outputs.

The system was calibrated for a specific environment: low light, a black table surface, a tripod-mounted camera overhead, and a projection wall near where guests naturally gathered. The camera, cables, and a closed door were present but never acknowledged.

Guests left traces without knowing they were being recorded.

Live projection — Processing sketch

Aggregate output — printed postcard (4×6, Canon Selphy CP1500)

Live Output

The Processing sketch projects onto a wall, starting black and silent until data arrives. When a stain is detected, it spawns a traveling shape — a semicircle or shooting line — that moves across the projection surface with a polygon grid trailing behind. Shapes fade over time, leaving a visual record of the session in progress.

Aggregate Output

At the end of the night, the accumulated database generates a 4×6 postcard printed on a Canon Selphy CP1500. Each print layers bands, arcs, and a polygon grid driven by session-wide averages of the five parameters. Every print is indexed and timestamped — a physical record of a single night's social behavior.

Process