Motion Detection And Movement Recognition In Classroom Video Environment

The automatically recording and broadcasting system based on image recognition technology, which can be used to improved quality and efficiency of the course recording has been one of the most important part of our country’s multimedia education. The key technologies are studied in this paper about how to detect moving object and recognize behavior in a classroom video environment.On the research of the motion detection, the algorithms of motion detection based on background model are detailed about their principles and efficiency. Then a background modeling and subtraction method by codebook construction is proposed. The CB algorithm adopts a quantization and clustering technique to construct a background model and subtract the current image from the background model to detect moving objects by color distortion and bright distortion. Additionally, an improved method based on CB is proposed. Evaluation shows that this algorithm is effective.On the research of the movement recognition, firstly moment invariant is introduced on its basic principle. Then the center coordinate and the size of the object are calculated by the zero-order and first-order moments of the binary image. Secondly the motion history image (MHI) is researched. And the orientation of each motion part is calculated by the MHI. At last, some motions appeared in classroom video environment are classified using features that have been extracted.