Perceiving Motion Cues Inspired by Microsoft Kinect Sensor on Game Experiencing
This work addresses enhancing user freedom and experience in HCI by integrating human cognitive factors, though it appears incremental as it builds on existing Kinect technology for specific applications.
The paper tackled the problem of replacing traditional mouse controllers with a Microsoft Kinect Sensor for human-machine interaction, achieving accurate hand gesture recognition and demonstrating efficiency through comparisons with mouse cursor accuracy and real-time performance in games like Fruit Ninja and Shape Touching.
This paper proposed a novel method to replace the traditional mouse controller by using Microsoft Kinect Sensor to realize the functional implementation on human-machine interaction. With human hand gestures and movements, Kinect Sensor could accurately recognize the participants intention and transmit our order to desktop or laptop. In addition, the trend in current HCI market is giving the customer more freedom and experiencing feeling by involving human cognitive factors more deeply. Kinect sensor receives the motion cues continuously from the humans intention and feedback the reaction during the experiments. The comparison accuracy between the hand movement and mouse cursor demonstrates the efficiency for the proposed method. In addition, the experimental results on hit rate in the game of Fruit Ninja and Shape Touching proves the real-time ability of the proposed framework. The performance evaluation built up a promise foundation for the further applications in the field of human-machine interaction. The contribution of this work is the expansion on hand gesture perception and early formulation on Mac iPad.