This chapter is about finding corresponding points and regions between images. Two different types of local descriptors are introduced with methods for matching these between images. These local features will be used in many different contexts throughout this book and are an important building block in many applications, such as creating panoramas, augmented reality, and computing 3D reconstructions.

The *Harris corner detection* algorithm (or sometimes the Harris & Stephens corner detector) is one of the simplest corner indicators available. The general idea is to locate interest points where the surrounding neighborhood shows edges in more than one direction; these are then image corners.

We define a matrix **M*** _{I}* =

Equation 2-1.

whereas before ∇*I* is the image gradient containing the derivatives *I _{x}* and

Let *W* be a weight matrix (typically a Gaussian filter *G _{σ}*). The component-wise convolution

Equation 2-2.

gives a local averaging of **M*** _{I}* over ...

Start Free Trial

No credit card required