Detecting objects and people with Support Vector Machines and histograms of oriented gradients

This recipe presents another machine learning method, the Support Vector Machines (SVM), which can produce accurate 2-class classifiers from training data. They have been largely used to solve many computer vision problems. This time, classification is solved by using a mathematical formulation that looks at the geometry of the problem in high-dimension spaces.

In addition, we will also present a new image representation that is often used in conjunction with SVMs to produce robust object detectors.

Getting ready

Images of objects are mainly characterized by their shape and textural content. This is the aspect that is captured by the Histogram of Oriented Gradients (HOG) representation. As its name indicates, this representation is based on building histograms from image gradients. In particular, because we are more interested by shapes and textures, it is the distribution of the gradient orientations...