Abstract: Aiming at the problem of low efficiency of train manual detection of pantograph status, a dynamic monitoring method of pantograph-catenary contact position based on video image is proposed. First, the image containing the pantograph-catenary obtained from the pantograph video captured by frame difference is used as the original training data set; then, the complex pantograph image background is segmented, and the super pixel segmentation is used to obtain the largest feature area, combining the HOG (Histogram of Directional Gradients) of the feature image to obtain the largest feature ROI (region of interest), to form the training data set, and to design the label; finally, the improved YOLOv3-tiny-strong network structure is used to detect the classifier and trained weight is used to monitor video targets. Results show that the dynamic monitoring method can accurately mark the position of the contact point of pantograph and catenary in each frame of image and can continuously capture the movement state of the pantograph, and effectively obtain the contact point and the pantograph relative coordinate position, so as to achieve the purpose of monitoring the pantograph, of which the detection accuracy can reach 98%.