In autonomous applications such as robotics or vehicles, using a camera to track the camera's position in space provides a useful localization estimate. Visual odometry analyzes sequential frames in a video and compares the movement of specific image features between them. Once correlations are found, a Kalman filter can be applied or a 3D map can be constructed, depending on the available data. While visual odometry provides a highly accurate measure of position, it is often used in conjunction with other localization and mapping techniques.