Classical Computer Vision: Labeling
Labeling Labeling is an image transformation that aims to turn the image into a model. In other words, it is a mapping function I -> M that will transform the input image into a model, that can be an array of numbers, a string, a graph, a set of images or whatever that makes sense to the problem being tackled. The goal here is to leave the pure image domain and finally enter into the meaning domain, by interpreting the image into a meaningful information. For example, given a photo, we want to detect that a car has crossed the cross-road on a red light. This final model information is a merely a boolean (True, crossed, False, didn't). Most of the algorithms are concerned with pattern recognition. As an example, let's try to label the following image. What we're interested here is to count how many "persons" are shown in this imag...