Perceiving Motion Cues Inspired by Microsoft Kinect Sensor on Game Experiencing

TL;DR

This paper introduces a Kinect-based gesture recognition system to replace traditional mouse controls, enhancing human-computer interaction with real-time, accurate motion perception demonstrated through game experiments.

Contribution

It presents a novel Kinect sensor-based method for gesture recognition, expanding hand gesture perception and initial application to Mac iPad interfaces.

Findings

High accuracy in gesture recognition compared to mouse control

Real-time performance demonstrated in Fruit Ninja and Shape Touching games

Potential for broader applications in human-machine interaction

Abstract

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.