In early days computers are operated by various interface devices, which are developed by the humans to interact with the computer. Starting from Punch-cards to touch screens man have changed the human life into an unimaginable state, right now we are stepping into an another era of computer technology, where the system makes things easier and simple and more powerful. A novel method of dynamic hand gesture recognition based on human computer interface intelligent system is proposed. The main aim is to interact with the computers without using mouse clicks and keystrokes. An architecture for hand posture, gesture modeling and recognition system is introduced, which is used as an interface to make possible communication with the sensory challenged (hearing impairment and gustatory impairment) people by simple hand gestures. The system transforms the preprocessed data of the detected hand into a fuzzy hand-posture feature model by using fuzzy neural networks. Based on this model, the developed system determines the actual hand posture by applying fuzzy inference. Finally, from the sequence of detected hand postures, the system will recognize the hand gesture of the user. Moreover, the computer vision techniques are developed to recognize a dynamic hand gestures that make interpretations in the form of commands or actions.
Quality of Service is an important attribute of a software system. In retrospect, performance assessment based on user interaction with the system has given a better understanding of underlying disciplines of the product. In this paper, we capture user interaction with the prototype/User Interface (UI). An approach for developing activity model from the user interface model is presented using workflows and functional elements. A methodology is proposed to transform UI into activity diagram. The approach is validated by an experimental setup using Amazon service. The performance of Amazon service is assessed using activity based performance prediction methodology, and the simulation results are obtained using SMTQA.
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