Gesture recognition using Kinect in a virtual classroom environment

In an E-learning classroom, students and professors are at different geographic locations. In the present E-learning system, the professor and the student interact with each other through simple internet applications. The disadvantage in this type of classroom set-up is that students in a remote location will not receive the same attention as those ones in a real classroom. Students in a remote location will only be seen on a small screen and the clarity of the video might be poor. Furthermore, the professor in a real classroom might focus only on students who are interacting face-to-face with him. The professor may not know the details of the remote students and how well they understand his class lecture. To solve this problem, this paper describes a system, based on KinectTM, to make the E-learning class lecture more interactive for the remote students. For example, when a student in a remote location, raises his/her hand to talk to a professor, the Kinect camera detects the student, identifies the gesture of the remote student, zooms onto the remote student, and displays details such as his/her name and background of study. Thus the professor can pay equal attention to both the remote and local students.

[1]  Debashis Ghosh,et al.  Mobile augmented reality based interactive teaching & learning system with low computation approach , 2013, 2013 IEEE Symposium on Computational Intelligence in Control and Automation (CICA).

[2]  Yasue Mitsukura,et al.  A robust gesture recognition based on depth data , 2013, The 19th Korea-Japan Joint Workshop on Frontiers of Computer Vision.

[3]  Yi Li,et al.  Hand gesture recognition using Kinect , 2012, 2012 IEEE International Conference on Computer Science and Automation Engineering.

[4]  James W. Davis,et al.  GESTURE RECOGNITION , 2023, International Research Journal of Modernization in Engineering Technology and Science.

[5]  Wilfried Philips,et al.  Detection of a hand-raising gesture by locating the arm , 2011, 2011 IEEE International Conference on Robotics and Biomimetics.

[6]  Greg Borenstein,et al.  Making Things See: 3D vision with Kinect, Processing, Arduino, and MakerBot , 2012 .

[7]  Junsong Yuan,et al.  Robust Part-Based Hand Gesture Recognition Using Kinect Sensor , 2013, IEEE Transactions on Multimedia.

[8]  Yangsheng Xu,et al.  Hand tracking and pose recognition via depth and color information , 2012, 2012 IEEE International Conference on Robotics and Biomimetics (ROBIO).