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#generative ai Open access

Pixel Dropping Method — Fixator Splitting System with Automatic Splitting and Reassembly — Full Version — Kinder Wunder

Oct 2026 · Zenodo (CERN European Organization for Nuclear Research)

Abstract

Pixel Dropping Method — Fixator Splitting System with Automatic Splitting and Reassembly — Full Version. Author: Kinder Wunder — Independent Researcher, Toronto, CA — Date: 03.10.2026 DOI: 10.5281/zenodo.23124833 — Category: G06T 13/00 Abstract: The method for character identity fixation in generative systems is proposed. The method is based on multi-level splitting of the body into reference zones with automatic splitting and reassembly. The method provides broad protection by covering any sign system (Arabic numerals, Roman numerals, UPPER/lower letters, icons). The zone is split into 4 to 20 points along closed contour clockwise or counterclockwise. The system automatically reconstructs invisible views from a single frame. Once fixed, the character can run and act without re-fixation. FILES INCLUDED (all authored by Kinder Wunder): 1. FIRST_FILE_Kinder_Wunder_CLEAN.pdf — Main method description with pixel economy (90% dropping inside nose zone, 0.08% of person pixels), broad claims 1-8, and figures FIG.1-FIG.3. 2. FINAL_Kinder_Wunder_CLEAN_NO_ABCD.pdf — Additional figures FIG.0-FIG.7 — Body split 1-7/S, Face Base P1-P6, Nose C1-C8 / C1-C10, Occiput e1-e4=24, Back S1-S5=40, Hand and Fingers as application of same principle. All files contain author name Kinder Wunder inside. All methods, codes, figures and terms Pixel Dropping, Fixator Splitting are intellectual property of Kinder Wunder. All rights reserved. Any commercial use, implementation, or AI training based on this method requires prior written permission. Contact via Zenodo record. Keywords: G06T 13/00, animation, character fixation, pixel dropping, fixator splitting, Kinder Wunder

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