The emergence of high resolution digital cameras for recording of still images and video streams has had a significant impact on how communication and entertainment have developed during the recent years. At the same time Moore’s law has made tremendous computing power readily available that only some 20 years ago was reserved for high profile research establishments and intelligence services. These two tendencies have respectively called for and fostered the advent of unprecedented computationally heavy image processing algorithms. Algorithms that in turn have allowed for new processing of existing image based material. Parallel to this technological development the measures deployed in the protection against attacks from the enemies of modernity calls for more surveillance of the public space. As a result of this regrettable circumstance more video cameras are installed in airports, on stations and even on open streets in major cities. Whether or not the purpose is entertainment or dead serious surveillance, tasks like detection and recognition of faces are solved using the same methods. Due to the varying and generally adverse conditions under which images are recorded there is a call for algorithms capable of working in an unconstrained environment. In 2004 an article by Paul Viola and Michael J. Jones titled “Robust Real-Time Face Detection” was publish in the International Journal of Computer Vision. The algorithm presented in this article has been so successful that today it is very close to being the de facto standard for solving face detection tasks. This success is mainly attributed to the relative simplicity, the fast execution and the remarkable performance of the algorithm. This report documents all relevant aspects of the implementation of the Viola-Jones face detection algorithm. The intended input for the face detection algorithm is any conceivable image containing faces and the output is a list of face positions.