Abstract: In order to solve the problem of cross-camera and full-scene vehicle spatial positioning in traffic applications,a method combining full-scene perspective stitching and 3D vehicle detection is proposed.Firstly,a method of automatic camera calibration in traffic scenes is proposed.By building a camera calibra-tion space model,the calibration parameters can be obtained and optimized automatically.Then,feature points in the overlapping area are used to transform and unify the multi-camera spatial coordinate system.In order to intuitively reflect the physical space of the whole scene,the perspective of each scene is trans-formed into a unified pixel-physical coordinate system.Finally,for the problem of 3D positioning of vehi-cles under monocular vision,an optimization model is established to construct a refined 3D bounding box by using the geometric constraints of vehicle projection.The 3D centroid is used as the vehicle spatial posi-tioning point,and the mapping to the pixel-physical coordinate system can reflect the dynamic information of vehicles.In the experimental environment with artificial feature points and the practical application envi-ronment without artificial feature points,the spatial positioning experiment is carried out for multi-type vehicles in cross-camera scene.Experimental results show that the algorithm can solve the problem of vehicle positioning in the large cross-camera scene of traffic video surveillance.The comprehensive positioning ac-curacy in the selected experimental scene can reach the centimeter level with a real-time performance.