That’s the book I’m currently reading and if you are interested in the field of the Data Visualization, this book is a good starting point.
The author is Ben Fry, the founder (with Casey Reas) of Processing, a programming language, and development environment. Initially created to serve as a software sketchbook and to teach fundamentals of computer programming within a visual context, Processing quickly developed into a tool for creating finished professional work as well.
Due to my attempt to create a perceptual interface using OpenCV, this post is the first in a series to explain briefly some of the capabilities of the OpenCV library, an open-source computer-vision library.
OpenCV comes with over 500 functions that cover many areas in vision, and its goal is to provide a simple-to-use computer vision infraestructure to build fairly sophisticated vision application quickly. The library is written in C and C++ and runs under Linux, Windows and MAC OS X. There is active development on interfaces for Phyton, Ruby, Matlab, and other languages.
Finding faces means finding complex objects, so OpenCV uses a statistical model (often called classifier), which is trained to find the object we are looking for. The training consists in a set of images, divided into “positive” samples and “negative” samples. The positive samples are instances of the object class of interest and the “negative”, images that don’t contain the object of interest.