CANONICAL COORDINATE INFRASTRUCTUREFOR SPATIAL COMPUTING

A persistent spatial reference layer for imaging, display, and spatial systems.

Master Frame Technologies is developing canonical coordinate infrastructure designed to establish persistent spatial relationships during data ingestion—before downstream rendering, viewport derivation, and related processing begin.

The objective is to provide a consistent, deterministic spatial-reference foundation for systems operating across changing display formats, orientations, devices, capture sources, rendering environments, and computational contexts.

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THE PROBLEM

Spatial relationships are often repeatedly translated.

Modern imaging, machine-perception, rendering, and spatial-computing systems frequently transform, reinterpret, or reconcile spatial information across different coordinate systems, orientations, viewports, aspect ratios, devices, and processing stages.

These transitions can require repeated transformation, normalization, buffer management, and application-specific handling. As systems become more complex, that work can increase implementation burden, memory traffic, processing overhead, latency, and opportunities for inconsistent spatial results.

THE MASTER FRAME APPROACH

Canonicalize once. Derive downstream.

Master Frame is developing a persistent computational substrate in which defined spatial and imaging relationships are established early in the data path.

Rather than requiring each display, viewport, orientation, or device context to independently redefine or reconstruct spatial relationships, downstream operations are designed to derive from a shared Master Frame reference.

CAPTURE / SENSOR / SOURCE

↓

WRITE-PATH CANONICALIZATION

↓

PERSISTENT MASTER FRAME REFERENCE

↓

DERIVED VIEWS / RENDERING / AI / XR / DEVICE CONTEXTS

ARCHITECTURAL PRINCIPLES

Write-Path Canonicalization

Defined coordinate relationships are established during initial data ingestion, rather than repeatedly reconstructed downstream.

Persistent Spatial Reference

Spatial relationships are designed to remain available independently of changing orientation, aspect ratio, viewport, rendering, or device context.

Deterministic Viewport Derivation

Views and spatial operations are designed to derive from a persistent reference rather than requiring repeated coordinate redefinition.

System-Level Applicability

The architecture is intended for evaluation across high-performance imaging, display, machine perception, XR, robotics, automotive vision, and related spatial-computing systems.

CURRENT STATUS

Patent applications have been filed directed to aspects of the Master Frame architecture.

Core concepts are being documented and evaluated through technical models, simulations, and ongoing implementation work.

Master Frame Technologies is selectively engaging qualified organizations regarding technical evaluation, design-partner discussions, platform licensing, and strategic partnerships. The Company is also engaging qualified seed investors with relevant deep-technology, infrastructure, or spatial-computing experience.

STRATEGIC ENGAGEMENT

We welcome inquiries from:

• Semiconductor, systems, and platform organizations

• Imaging, display, machine-perception, and spatial-computing teams• Qualified technical collaborators and design partners

• Strategic partners and licensing counterparties

• Seed investors with deep-technology, infrastructure, or spatial-computing focus

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robert@masterframetech.com

MASTER FRAME TECHNOLOGIES, INC.

Patent applications are pending. Proprietary technical information is shared selectively and under appropriate confidentiality arrangements.