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Introduction to AI

Machine Learning

Deep Learning

Generative AI

Tools & Frameworks

General

3D Reconstruction - Building Scenes from Images

3D reconstruction turns photographs or video into a representation of scene geometry. The result may be a sparse point cloud, dense mesh, depth map, or a neural representation that can render new views.

Multi-View Geometry

When a scene is viewed from multiple camera positions, corresponding image points constrain their 3D location. A traditional pipeline is:

  1. detect and match visual features across images
  2. estimate camera poses with structure from motion
  3. triangulate matched points into a sparse cloud
  4. densify the cloud and reconstruct a surface

Accurate camera calibration, overlap, texture, and varied viewpoints are essential. A blank wall supplies too few reliable features; a glossy object can produce inconsistent matches.

Representations

RepresentationStrengthTradeoff
Point cloudSimple, captures measured locationsNo explicit surface
MeshEasy to render and editSurface extraction can be fragile
Voxel gridRegular 3D structureMemory grows quickly with resolution
Neural fieldHigh-quality novel viewsTraining and rendering can be costly

Neural radiance fields (NeRFs) learn a function that maps 3D position and view direction to color and density. They can render convincing new views but do not automatically provide a clean, physically accurate mesh.

Measuring Quality

For known geometry, compare predicted and reference surfaces with Chamfer distance, point-to-surface distance, or completeness. For novel-view synthesis, use held-out camera views and image metrics alongside human inspection. Visual realism alone can hide missing or distorted geometry.

Practical Capture Guidance

Walk around the object with consistent exposure, include overlap between images, avoid motion blur, and record calibration information. Reconstruction is especially unreliable for transparent, reflective, thin, or moving objects. In surveying, healthcare, or robotics, validate scale and accuracy against physical measurements rather than trusting a rendered scene.