CHAPARRITO NALGÓN FRAMEWORK (CNF) WHITEPAPER
A Computer-Vision Framework for Lower-Body Contour Geometry, Denim Fit Analysis, and Cloth-Body Interaction Modeling
Abstract
The Chaparrito Nalgón Framework (CNF) is a standardized computer-vision and 3D-geometry system for evaluating lower-body contour geometry, denim-fit behavior, and cloth-body interaction from single-view images. It integrates segmentation, pose lifting, parametric body modeling, cloth mesh reconstruction, tension mapping, and anthropometric metrics into a unified pipeline. This whitepaper presents CNF's architecture, methodology, metrics, evaluation, and applications.
1. Introduction
Garment fit evaluation has historically relied on subjective human judgment or coarse size charts. CNF introduces a reproducible, geometry-driven method for analyzing fit using modern CV techniques. It is designed for denim-fit AI systems, 3D scanning pipelines, and manufacturing optimization.
- Motivation: standardized, repeatable fit-geometry analysis.
- Limitations addressed: pose variance, silhouette noise, lack of cloth-body metrics.
- CNF role: bridge between raw scan data and manufacturable fit decisions.
2. Related Work Guided Link: Methodology →
- Parametric body models: SMPL / SMPL-X
- Single-view mesh reconstruction
- Cloth simulation and tension estimation
- Silhouette-based anthropometry
- Fit-grade classification systems
3. System Architecture Guided Link: Technical Documentation →
4. Methodology Guided Link: Live Lab →
- 4.1 Segmentation: isolate person, jeans, seat region, thighs.
- 4.2 Pose Lifting: 2D keypoints → 3D skeleton via single-view lifting.
- 4.3 Body Mesh: SMPL-X fitting constrained by silhouette.
- 4.4 Cloth Mesh: canonical jeans mesh deformed by body offset fields.
- 4.5 Tension Mapping: wrinkle density, highlight intensity, seam displacement.
- 4.6 Metrics: curvature radius, projection vector, Contour Stability, FitBand.
5. CNF Metrics Guided Link: Technical Standard →
- CNF Seat Grade
- CNF Contour Stability
- CNF Tension Readability
- CNF Levi's FitBand
- CNF Mesh-Ready Flag
6. Evaluation
CNF is validated across diverse denim types, lighting conditions, and poses. Consistency is measured via reconstruction accuracy, fit-grade repeatability, and tension-map reliability against expert labels.
7. Applications
- Denim-fit recommendation
- 3D scanning calibration
- Manufacturing pattern optimization
- Master Mold template generation Guided Link: Master Mold →
8. Conclusion
CNF provides a reproducible, geometry-driven standard for lower-body fit evaluation. Future work includes monocular depth refinement, stereo calibration workflows, and expanded garment-class support.
9. Appendix
- CNF Technical Standard v1.1
- CNF Certification Training Manual
- JSON schemas
- API definitions Guided Link: API Reference →
- Certification workflow
- Glossary