Nowadays, the general topic of human face detection becomes a very important research field. This is due to the needs of good working face detection methods have reached a high level and the current systems do have a high optimisation potential. In this master thesis, a hybrid real-time face detection system will be introduced that is able to deal with colour images in HD resolution. This system is able to detect multiple faces on a single input image and consists of three main components, motion detection, skin colour detection and applying an Adaboost algorithm. In the first stage, all moving regions will be extracted. Afterwards, these moving regions will be analysed if skin colour is present and finally, the Viola Jones method is applied on the regions of interest to detect human faces. The motion detection bases on the background subtraction method that separates the background from the foreground. For the skin colour detection, four different colour spaces (RGB, normalised RGB, HSV, YCbCr) are used by applying predefined rules on pixel areas to detect skin colour. After some test runs, the application shows respectable results for frontal face detection in different environmental conditions.