Multi-student standing and sitting detection method based on optical flow and k-means clustering

The invention discloses a multi-student standing and sitting detection method based on an optical flow and k-means clustering, and the method comprises the steps: collecting image information of a student region; carrying out the moving object region detection for the student region, detecting a moving region in an image through an inter-frame difference method, and marking a moving object region template through a connection domain marking algorithm; enabling the moving object region template to be superposed with an original image, carrying out the optical flow calculation of the moving object region, and obtaining a motion vector of a feature point; enabling the optical flow to be divided into an upward group A and a downward B, and carrying out the clustering; determining that the object performs standing and sitting motions if the number of continuous appearing times of the same central point reaches a certain value, and ending the detection at this moment. Compared with the prior art, the method can achieve the detection of the standing and sitting behaviors of the students through one camera, and the equipment is simple and easy to install. The method is suitable for various types of environments. The method is high in detection accuracy, is better in instantaneity, and can achieve the class demands. The method can achieve the detection of simultaneous standing condition of a plurality of students, and is more practical.