As contribution the research study as outcome developed a software application and programmed several new recognition gestures and presented a set of tools supporting the spectrum of software engineering natural user interfaces to be used in University promotion and marketing. This research study tries to foster several contributions. Firstly, this system is built on basis of separate library used for the gesture recognition part of the application, which can also work separately from the system and can be used in different contexts. It is very extendable and allows the users to implement new gestures on top of the library, thus enriching its context and provides easy start for the user allowing him to concentrate to the business logic instead of the low level programming of the gesture recognition algorithms. Secondly, in addition to the basic gestures, created are several other gestures that add additional value to the library itself. New gestures that are added to the library are DownSwipe, UpSwipe, ClockwiseCircle, CounterClockwiseCircle, Push gestures, ManualDoorOpen gesture, AutomaticDoorOpen gesture and WalkingGesture. Thirdly, this research also contributes to researchers and professionals who are dedicated to a research in the area of natural user interfaces and their efforts in finding an effective algorithm for human gesture recognition. This research investigates different approached to gesture recognition, such as Record and recognize approach, Neural Networks approach and Gesture composition approach, presented which are their advantages and weaknesses and presented why chosen is the Gesture Composition approach.