Location Determination of Dynamic Objects Using a Single CCTV with Monocular Depth Estimation

Abstract. This contribution presents a method to determine ground coordinates of pedestrians from a single CCTV frame using monocular depth estimation and orthophoto-based ground control points. Urban crowd monitoring requires pedestrian location information, but many CCTV-based approaches rely on accurate camera calibration or multi-view configurations, which are often unavailable in real deployments. In this study, we exploit relative depth values from a monocular depth estimation model (Depth Anything V2) and ground control points jointly identifiable in both the CCTV frame and an orthophoto in EPSG:5186. For each frame, depth-based distance ratios between the pedestrian and ground control point pairs are used to construct Apollonius circles in the orthophoto plane, and the pedestrian position is estimated by a weighted least-squares adjustment of their intersections. The method is evaluated on 180 frames across two scenes from an urban testbed with camera–target distances within approximately 50 m, across three GCP placement scenarios. For the optimal configuration (Scenario A), a mean RMSE of 1.989 m was achieved, excluding frames in which GCPs were temporarily occluded by moving objects, demonstrating that single-frame CCTV imagery combined with an orthophoto can achieve an accuracy of approximately 2 m without any EOP/IOP information, which is practically useful for urban crowd monitoring and dynamic thematic mapping. The influence of GCP placement geometry and occlusion conditions on estimation accuracy is also analyzed.