Content-aware streaming of lecture videos over wireless networks

Video streaming over wireless networks becomes increasingly important in a variety of applications. To accommodate the dynamic change of wireless networks, quality of service (QoS) scalable video streams need to be provided. This paper presents a system of content-aware wireless streaming of lecture (instructional) videos for e-learning applications. A method for real-time analysis of instructional videos is first provided to detect video content regions and classify video frames, then a \´leaking video buffer" model is applied to dynamically compress video streams. In our content-aware video streaming, instructional video content is detected and different QoS are selected for different types of video content. Our adaptive feedback control scheme is able to transmit properly compressed video streams to video clients not only based on wireless network bandwidth, but also based on video content and the feedback of video clients. Finally, we demonstrate the scalability and content awareness of our system and show experimental results of two lecture videos.