CASE STUDY / C++ / PERLIN NOISE / VOXEL TERRAIN
Procedural Terrain / C++
A C++ learning project building voxel terrain from noise. Beyond the basic OpenGL setup, the source includes multi-scale terrain synthesis and an isometric rendering experiment.
- 3 layers
- Separate continental, mountain, and detail scales
- Seeded
- Seeded permutation-table construction
- C++
- Public noise, generation, rendering, and profiling helpers
ROLE & CONSTRAINTS
The problem and my scope.
Solo project. C++ generation and rendering, using GLFW/GLAD for OpenGL and SFML for the isometric demo.
How can a generator provide separate controls for broad landforms, mountains, and fine detail?
DESIGN DECISIONS / SOURCE EVIDENCE
Follow the implementation.
Compose multi-octave Perlin noise
Implement a seeded permutation table, gradients, interpolation, and octave accumulation. Combine continental, mountain, and detail bands with different frequencies and amplitudes, clamp heights, then assign block types.
src/terrain.cpp / PerlinNoise & generateTerrain ↗Generate beyond the stored region
The isometric view can query blocks outside its stored terrain using matching seed and generation parameters. A PerlinNoise object is retained until the seed changes, avoiding reconstruction on each query. No measured speedup is claimed.
src/isometric_terrain.cpp / getBlockAtWorld ↗Separate instrumentation from evidence
A profiler helper tracks FPS and elapsed time. Having instrumentation is different from publishing a controlled comparison: no common-condition benchmark dataset is currently included.
src/performance_profiler.h ↗LIMITATIONS & NEXT QUESTION
Limits and the next question.
- Reproducibility assumes the same implementation and environment. Cross-platform equality of C++ library shuffling has not been verified.
- Generation alone does not establish traversability or playability. This project has no published navigation-based evaluation.
- Rendering performance, memory use, and multi-seed quality comparisons are not published. This is a learning project, not a published research result.
I want to study how generation parameters affect reachability and path length, evaluating terrain and agent movement together. The new browser lab is a separate experiment toward that workflow.
REPRODUCTION / READING GUIDE
Inspect and reproduce.
Targets are taken from the public Makefile. The native setup needs macOS, clang++, GLFW/GLAD, SFML, GLM, and pkg-config as applicable. The browser demo is not a port of this C++ project.
make terrain
make run-terrain
# SFML isometric view
make isometric
make run-isometricThe case study refers to a fixed public source revision, README, and project logs inspected on November 1, 2026.
FROM SOURCE TO EXPERIMENT