Computer Vision: Foundations and Geometric Principles

Computer Vision (CV) is the field of Artificial Intelligence that enables computers to interpret and understand the visual world. It is deeply rooted in [Linear Algebra](LinearAlgebra) and projective geometry.

1. Image as Matrix

At its core, a digital image is a multi-dimensional matrix of pixel values. Operations like convolution and pooling are fundamentally linear transformations applied across these matrices.

2. Geometric Transformations

CV relies heavily on affine and perspective transformations to map 2D images to 3D spatial coordinates, a process essential for autonomous navigation and robotics.

For more on the underlying math, see [Linear Algebra](LinearAlgebra).