Author: Muhammad Ali
Position: Independent Researcher / CNC Systems Designer
Location: Rawalpindi, Pakistan
Date: February 2026
License: MIT License
This paper proposes Scalable Vector Global Video (SVGV), a paradigm shift in digital media processing. By moving away from raster-based pixel grids and adopting a coordinate-based geometric model, SVGV solves the twin problems of Data Poverty and Sensor Noise (Digital Trash). The system utilizes real-time Bézier path extraction to reduce file sizes by up to 85% while providing infinite resolution, allowing high-fidelity consumption of content (e.g., K-Dramas) on budget mobile hardware.
Current video standards (H.264/H.265) are “pixel-heavy.” On budget mobile devices common in developing regions:
- Storage/Data: A single 1080p episode can exceed 1.5GB, making it inaccessible to users on limited data plans.
- Fidelity: Digital zoom results in pixelation and “trashy” artifacts.
- Hardware: Budget GPUs struggle to render high-bitrate AI-enhanced video without thermal throttling.
Drawing inspiration from CNC Toolpathing (G-code/Vectric Aspire), SVGV treats every frame as a collection of mathematical paths rather than a grid of colored dots.
Unlike standard vectorizers that blur fine details, the Anti-Trash Lock identifies “High-Frequency Interest Zones” (eyes, lips, and textures).
- It applies a Bilateral Pre-Filter to remove sensor grain.
- It locks the coordinate precision for facial features while simplifying background paths.
The engine utilizes a Tile-Based Approach to fit within the L1 cache of mobile GPUs (Mali/Adreno):
- Deconstruction: The frame is split into 16×16 tiles.
- Path Extraction: GPU cores execute parallel scanline tracing to identify contours.
- Quantization: Math is performed in Float16 (FP16) to double speed on “trashy” hardware.
To run on a phone with 2GB-4GB of RAM, SVGV employs Heterogeneous Computing:
- NPU: Handles saliency detection and the Fidelity Lock.
- GPU: Handles Bézier path generation and rendering via Vulkan/OpenGL ES.
- Delta-Compression: Only moving coordinates are updated; static backgrounds are cached as persistent vector layers.
- Education: Entire semester libraries can be stored in the space of a single movie.
- Legacy: Family videos and historical archives become “future-proof” for 8K/16K displays.
- Hardware Equality: A $100 phone captures and displays video with the clarity of a $1,000 device.
SVGV is not just a codec; it is a democratization of visual data. Future research will focus on the SVGV-NDK SDK, allowing developers to integrate vector-video into existing apps without high CPU overhead.
Open Source Contribution: This research is dedicated to the global developer community. I am currently seeking a C++/NDK partner to move from theoretical logic to a functional Android MVP.