OpenCV: Computer Vision Projects with Python

Tracking faces

The challenge in using OpenCV's Haar cascade classifiers is not just getting a tracking result; it is getting a series of sensible tracking results at a high frame rate. One kind of common sense that we can enforce is that certain tracked objects should have a hierarchical relationship, one being located relative to the other. For example, a nose should be in the middle of a face. By attempting to track both a whole face and parts of a face, we can enable application code to do more detailed manipulations and to check how good a given tracking result is. A face with a nose is a better result than one without. At the same time, we can support some optimizations, such as only looking for faces of a certain size and noses in certain ...