Teaching Video Compression Algorithm Based on Key Frame and Indicator Movement Model

To improve teaching video compression ratio and production efficiency, considering that effective information of teaching video normally remains for a long time and locates in fixed area, a teaching video compression algorithm based on key frame detection and indicator movement modeling is proposed. Firstly, the projection area is detected as the effective region of each frame to reduce the knowledge redundancy. Then, the type of each frame is determined using change detection, and the indicator motion model is established for the mouse cursor and the laser point to reduce more knowledge redundancy. Finally, a corresponding play algorithm based on the key frame coding and indicator motion model is designed to replay the videos by use of OpenCV and MFC. The experimental results showed that, for the teaching videos with effective information in the projection arca, the proposed method achieved an average of 88% bitrate reduction than that of H. 264 under the same peak signal to noise ratio value. Besides, the encoding and decoding efficiency of this algorithm could meet the real-time requirement. Without extra manual editing, the production and transmission efficiency of online courses could be significantly increased.