Modeling Workflows

CONTEXT

📖2 min read

Introduction

Within the polygonal modeling space, there are distinct ways to generate or manipulate meshes. These fall into logical categories based on who or what drives the geometry creation: you, the computer, or the real world.

Understanding these distinct workflows allows you to choose the right tool for the specific task at hand, whether it requires manual precision, algorithmic complexity, or real-world capture.

Manual Generation

(Human-driven, direct control over geometry)

Direct Modeling

Manual manipulation of vertices, edges, and faces. The foundation of all polygonal modeling with the highest level of control.

Subdivision Surfaces

Model a low-poly cage and let algorithms calculate smooth surfaces. The bridge between polygonal control and organic curves.

Sculpting

Brush-based workflow for organic forms. Push, pull, and shape geometry like digital clay.

Kitbashing

Composing complex forms by combining pre-existing geometric shapes. Mostly used for building a speed-focused base-line model.

Boolean Operations

Define geometry by adding, subtracting or intersecting overlapping volumes rather than manipulating vertices.

Algorithmic Generation

(Computer-driven, rule-based geometry)

Procedural Modeling

Define rules or algorithms that Blender follows to generate geometry. Non-destructive and, in a way, parametric.

Simulation

Physics-based deformation for soft bodies and destruction. Simulates forces to create organic folds or distortions.

Generative AI

Neural networks predicting 3D topology from 2D data. Rapidly evolving into a standard drafting tool.

Captured Generation

(Real-world data converted to geometry)

Structure from Motion

Deriving geometry from the real world via, for example, photogrammetry methods or LiDAR scanning.

The Unifier

(Bridging all workflows back to clean polygonal meshes)

Retopology

Building optimized polygonal meshes over existing objects. The key bridge that can standardize many sources of data into geometric data.

Summary

Choosing the right workflow is about understanding the source of your data and the level of control you need. While manual generation offers the most precision, algorithmic and captured workflows can save immense time when used correctly.

Key Takeaways:

Manual Generation: Best for precision, control, and clean topology.
Algorithmic Generation: Ideal for complex, rule-based structures and non-destructive iteration.
Captured Generation: The most accurate way to represent existing real-world objects.
Retopology: The essential step to unify different geometry sources into a clean, usable mesh.

Introduction​

Manual Generation​