Title : 
Real-time hand gesture recognition with Kinect for playing racing video games
         
        
            Author : 
Yanmin Zhu ; Bo Yuan
         
        
            Author_Institution : 
Intell. Comput. Lab., Tsinghua Univ., Shenzhen, China
         
        
        
        
        
        
            Abstract : 
This paper presents a Kinect based hand gesture recognition system that can effectively recognize both one-hand and two-hand gestures. It is robust against the disturbance of complex background and objects such as the faces and hands of other people by exploiting the depth information and carefully choosing the region of interest (ROI) in the process of tracking. The recognition module is implemented using template matching and other light weight techniques to reduce the computational complexity. In the experiments, this system is tested on real world tasks from controlling the slide show in PowerPoint to playing the highly intense racing video game Need for Speed. The practical performance confirms that our system is both effective in terms of robustness and versatility and efficient for various real-time applications.
         
        
            Keywords : 
computer games; gesture recognition; human computer interaction; image matching; interactive devices; HCI; Kinect; Need for Speed; ROI; human-computer interaction; racing video games; real-time hand gesture recognition; recognition module; region of interest; template matching; Games; Gesture recognition; Image color analysis; Lighting; Sensors; Skin; Trajectory; Kinect; hand gesture recognition; video games;
         
        
        
        
            Conference_Titel : 
Neural Networks (IJCNN), 2014 International Joint Conference on
         
        
            Conference_Location : 
Beijing
         
        
            Print_ISBN : 
978-1-4799-6627-1
         
        
        
            DOI : 
10.1109/IJCNN.2014.6889481