In order to simplify the three-dimensional measurement and solve the baseline limitation problem in traditional stereo vision methods, a method based on single-camera micro-angle rotation combined with neural network for three-dimensional measurement is proposed. The method gathers two-dimensional image data by rotating a single camera at a small angle. Additionally, the three-dimensional spatial coordinates are established by moving the chessboard calibration target with an electric sliding table. Based on the idea of camera linear imaging model, where the projection matrix represents the mapping relationship between image coordinates and 3D coordinates is replaced by BP neural network. It obtains the direct mapping from 2D coordinates to 3D coordinates and realizes 3D measurement under micro baseline. The experimental results show that the absolute error of the proposed method is 0.0864mm compared with the distortion measured by the traditional method. This method integrates neural network into the single-shot vision field, which can make up for the defects of traditional vision measurement methods in micro baseline scene. It has potential application value for mobile equipment, monitoring equipment and 3D information acquisition in narrow scenes.