Environmental conditions such as wind and ground traffic will introduce motions in camera systems, which contribute as noise and thus affect measurement accuracy. The conventional camera motion correction methods need to track static reference objects by one or multiple cameras, reducing applicability and increasing costs. This study proposes a novel 6-degree-of-freedom (DOF) camera motion correction method based on an inertial measurement unit (IMU) sensor. The Kalman filter is adopted as a data fusion method to estimate the camera orientation and translation. Six pinhole camera models are built to evaluate and correct 6-DOF camera motions. The system hardware configuration is detailly introduced. The motion correction efficiency and robustness have been tested under different object distances and focal lengths. The motion correction ratio has been statistically analysed and achieved approximately 80%. The object distance has little effect on the correction ratio.