Spray production line trajectory planning and spray robot self programming technology are based on the workpiece online measurement. As a costeffective threedimensional imaging device, TOF camera has been applied to workpiece measurement in recent years. Aiming at the problem that existing TOF camera in terms of limited field of imaging view and single image can only obtain local contour depth information. A method of 3Dobject modeling based on GPUaccelerated computing and TOF point cloud streaming is proposed. The main algorithm is signed distance function (SDF) point cloud fusion, then spatial hashing storage is used to manage massive point cloud data, meanwhile, fast odometry from vision (FOVIS) system for pose estimation is introduced to improve the efficiency and robustness of insitu 3Dobject modeling algorithms of workpices. The experimental results on simulation platform of spraying production line show that the average number of frames in the modeling process can reach 58 frames per second, failure rate less than 2%, graphic memory usage rate about 25%, provides complete point cloud data for subsequent 3D measurement and spray traajectory planning.