Congratulations! You now have a good understanding of how 3D rendering works. You’ve created a raytracer and a rasterizer and gained a good conceptual understanding of the algorithms and math that power them.
However, as I explained in the introduction, it’s impossible to cover the entirety of 3D rendering in a single book. Here’s a few topics you might want to explore on your own to expand your horizons:
- Global illumination, including radiosity and path tracing
Find out how deep the “ambient light” rabbit hole goes!
- Physically based rendering
Illumination and shading models that don’t just look good, but model real-life physics.
- Voxel rendering
Think Minecraft, or MRI scans in hospitals.
- Level-of-detail algorithms
This includes offline and dynamic mesh simplification, impostors, and billboards. These algorithms are how we efficiently render forests with billions of plants, crowds of millions of people, or extremely detailed 3D models.
- Acceleration structures
This includes binary space partition trees, k-d trees, quadtrees, and octrees. These structures help efficiently render massive scenes, such as an entire city.
- Terrain rendering
How to efficiently render a terrain model that might be as big as a country yet have human-scale detail.
- Atmospheric effects and particle systems
Fog, rain, and smoke, but also some less intuitive materials like grass and hair.
- Image-based lighting
Similar to environment mapping, but for diffuse lighting.
- High dynamic range, gamma correction
The color representation rabbit hole also goes deep.
Also known as “the moving white patterns at the bottom of the swimming pool.”
- Procedural generation of textures and models
Add more variety and possibly infinitely big scenes.
- Hardware acceleration
Using OpenGL, Vulkan, DirectX, and others to run graphics algorithms on GPUs.
Of course, there are many other topics, and that’s just 3D rendering! Computer graphics is an even broader subject. Here are some areas you might want to investigate:
- Font rendering
This is surprisingly more complex than you might think.
- Image compression
How to store images in the least amount of space.
- Image processing (e.g. transforming and filtering)
Think Instagram filters.
- Image recognition
Is that a dog or a cat?
- Curve rendering, including Bezier curves and splines
Find out what these weird arrows on the curves of your favorite drawing program really are!
- Computational photography
How does the camera on your phone take such good pictures with almost no light?
- Image segmentation
Before you can “blur the background” of your video call, you need to determine which pixels are background and which aren’t.