Abstract: In response to the problem that traditional video surveillance relies on manual analysis of data to determine the motion trajectory of dynamic targets, which wastes a lot of resources and has poor real-time performance, a pedestrian trajectory determination method based on object-image distance conversion matching is proposed. The dynamic conversion scale factor k between the image-to-object plane was obtained using the anchor frame and pedestrian height data and combined with the length of the corresponding moving image element in the video to obtain the distance of the pedestrian in real geospatial space and then compared with the map API route distance measurement to determine the pedestrian’s movement. In addition, the trend of the dynamic scaling factor k allowed the detection of wandering behavior during pedestrian movement and the correction of deviations from the route. It is demonstrated that the method can remove the influence of irregular pedestrian movements on the trajectory determination, providing a new solution for the trajectory determination of cross-camera motion targets.