SPC · Semantic Point Cloud Codec · v0.2
Reference Implementation Complete
Genesis Venture Studios  ·  Compression Technology  ·  April 2026

Semantic Point
Cloud Compression

Semantic-aware codec for organized point cloud data. Built for LiDAR. Runs on existing DSP hardware. No new silicon required.

250:1 Rigid Object
1,200:1 Articulated
4,800:1 Predictive Delta

Measured results · Phase 0 proof of concept · April 2026 · Standard laptop · No GPU · No specialized hardware

// Problem Statement

Raw LiDAR bandwidth is the ceiling.

Organized point cloud sensors produce 24KB per frame at 30Hz regardless of scene activity. Standard compression achieves 3–5x. The interface load is near capacity on every frame — even when nothing is happening.

SPC changes the question. Instead of compressing what the sensor sees, SPC stores only what changed from a known reference. A stable surface transmits zero bytes. A detected anomaly transmits a 12-byte alert with exact coordinates.

The system is silent until something matters.
// Phase 0 Results — Measured, Not Modeled
Metric Result Notes
Rigid object compression 250:1 Confirmed — Test 1
Articulated body (5-joint) 1,200:1 Confirmed — Test 3
Predictive delta (full stack) 4,800:1 Confirmed — Test 4
Reconstruction error 0.0032 mean Sub-millimeter, zero drift
Encode speed 0.46ms / frame 70× under 30fps budget
Cold start (new object) 2 frames (66ms) Auto-catalogued
Encode platform Standard laptop No GPU required

// All results from a single Python implementation on commodity hardware. No specialized processing units.

// Target Applications
Space Structures

ISS hull monitoring. Spacecraft skin integrity detection. Flash LiDAR on existing flight hardware. Silence until breach detected.

TRL-9 Hardware In Orbit
Airborne Platforms

In-flight structural monitoring. 66ms breach detection on wing surfaces. Runs on existing avionics DSP. No new hardware integration required.

DSP-Native
Marine Systems

Continuous hull integrity monitoring at near-zero bandwidth. Organized grid format. Works on existing sonar processing hardware.

Near-Zero Bandwidth
Articulated Bodies

Human and mechanical body capture. 4,800:1 on predictive walking gait. Defense, robotics, simulation, and training applications.

Defense · Robotics
// Implementation Status
spc-reference · v0.2.0
Format Specification · v0.2 — FROZEN
Reference Implementation · COMPLETE
Conformance Suite (§12) · VALIDATED
Test Coverage · 752 tests passing
Payload Compression · TYPE_TRANSFORM · SKELETAL · DELTA · REF_ADD
Domain Profiles · LIDAR · FLASH · SURVEY · MEDICAL · ARTICULATED · FORENSIC
Platform · Python 3.10+ · Zero runtime dependencies
CLI · spc encode · spc decode · spc inspect

Conformance suite validates all 12 §12 requirements from the frozen v0.2 format specification. Implementation notes maintained as a numbered decision log (D-001 through D-016).

// Intellectual Property

Proprietary IP

SPC is proprietary technology developed by Genesis Venture Studios. The compression architecture, semantic matching methodology, and reference library system are protected as trade secrets under the Defend Trade Secrets Act (2016).

Access to the technical specification, format documentation, and reference implementation source requires a signed NDA and IP agreement prior to any disclosure.

Engineering contact only. No sales process. If you are evaluating point cloud compression for a specific program, reach out with a one-line description of your use case.

How to Access
01 Contact via email below with your use case
02 Sign NDA + IP agreement
03 Receive format specification and implementation
04 Integration support available

Ready to Evaluate SPC

NDA first.
Technical spec after.

Engineering contact only. If you are evaluating point cloud compression for a specific program, send a one-line description of your use case. Response within 48 hours.

Genesis Venture Studios  ·  Texas  ·  genesisvcs.com