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Ray Tracing

A rendering technique that simulates the physical behavior of light by tracing the path of light rays as they interact with surfaces.

What is Ray Tracing?

Ray tracing is a rendering algorithm that produces highly realistic images by simulating the actual physics of light transport. The technique works by tracing the path of light rays from a virtual camera through each pixel of the image, calculating how those rays interact with surfaces in the 3D scene through reflection, refraction, and absorption.

Unlike rasterization techniques that approximate lighting effects, ray tracing accurately captures complex optical phenomena. When a ray hits a reflective surface, the algorithm spawns new rays to trace the reflection. Transparent materials generate refracted rays that bend according to their index of refraction. This recursive process continues until rays either exit the scene or their contribution becomes negligible.

The computational intensity of ray tracing historically limited its use to pre-rendered images and animations. Each pixel might require tracing thousands of rays to achieve noise-free results, with render times measured in hours for complex architectural scenes. Recent advances in GPU hardware and denoising algorithms have made real-time ray tracing increasingly viable.

For architectural visualization, ray tracing excels at rendering materials like glass, water, polished stone, and metallic surfaces where accurate reflection and refraction are essential. It naturally produces soft shadows from area light sources, caustic patterns from focused light, and the subtle interplay of light between surfaces that makes rendered spaces feel real.

Examples in Practice

  • Glass curtain wall renderings with accurate reflections and transparency
  • Interior scenes with complex mirror and polished surface interactions
  • Swimming pool visualizations with realistic water caustics
  • Jewelry store designs with precise gemstone light behavior

How This Relates to AI Visualization

Modern AI rendering leverages ray tracing principles while using neural networks to intelligently denoise and complete images, achieving photorealistic results in a fraction of traditional render times.

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