Abstract: To address the issues of large drift errors and low calculation accuracy in inertial navigation methods, as well as significant posture recognition errors in visual methods due to camera interference from dust and equipment obstructions, a method of support posture perception in mining face based on visual-inertial information fusion was proposed. First, four feature points of infrared targets were fixed to the base platform of the support, and binocular cameras were fixed to the support top beam and shield beam. A target recognition method based on Canny and least squares, along with a BA-PnP algorithm based on four feature points, was used to solve the pitch and roll angles of the top beam and shield beam relative to the base. Then, an inertial measurement unit (IMU) was fixed to the hydraulic support top beam, shield beam, and base. The complementary filtering method of the MEMS gyroscope and accelerometer in the IMU was used to solve the pitch and roll angles of the top beam, shield beam, and base in the world coordinate system. Finally, the posture angles calculated by the visual system and the inertial navigation system were fused using the extended Kalman filter for multi-source information fusion. The low-frequency stability of the vision information was used to suppress the accumulated errors of the IMU, resulting in accurate posture perception of the mining support. Three methods for support posture perception, based on vision, inertial navigation, and visual-inertial information fusion, were compared in experimental results. The findings showed that: ① In the initial stationary state, all three methods had high accuracy, but as the support operation cycles increased, the vision-based and inertial navigation-based results gradually deviated from the true values. ② The root mean square errors (RMSE) of pitch angle perception for the top beam relative to the base were 0.201°, 0.190°, and 0.081° for the vision-based, inertial navigation-based, and visual-inertial information fusion methods, respectively. For the shield beam relative to the base, the RMSE of pitch angle perception were 0.340°, 0.297°, and 0.162°, respectively. ③ The RMSE of the hydraulic support column extension length calculated by the visual-inertial information fusion method was 13.682 mm, meeting on-site requirements. The visual-inertial information fusion-based support posture perception method could provide more accurate posture parameters for the intelligent control of hydraulic supports.