Pose estimation has always been a key issue in the field of 3D reconstruction. A tightly coupled real-time pose optimization method for the mobile terminal is proposed to ensure the real-time performance under the limited resources of the mobile terminal and improve the accuracy of trajectory calculation. First, image information and motion sensor information are obtained to conduct pretreatments such as feature extraction and pre-integration. Then, the reprojection error and the inertial sensor error are calculated according to the epipolar geometric constraints. Finally, the weighted error is used to jointly optimize the calculation of the pose trajectory. The tight coupling strategy can efficiently use the consistency in the pose constraint of image information and inertial motion information. Experiments on the public data set EuRoC show that compared with the existing visual-inertial pose estimation methods, the proposed method guarantees the real-time performance on the mobile terminal and has a smaller camera trajectory error in reconstruction.