  In simultaneous localization and mapping (SLAM), image feature point matching
process consume a lot of time. The capacity of low-power systems such as
embedded systems is almost limited. It is difficult to ensure the timely
processing of each image information. To reduce time consuming when matching
feature points in SLAM, an algorithm of using inertial measurement unit (IMU)
to optimize the efficiency of image feature point matching is proposed. When
matching two image feature points, the presented algorithm does not need to
traverse the whole image for matching feature points, just around the predicted
point within a small range traversal search to find matching feature points.
After compared with the traditional algorithm, the experimental results show
that this method has greatly reduced the consumption of image feature points
matching time. All the conclusions will help research how to use the IMU
optimize the efficiency of image feature point matching and improve the
real-time performance in SLAM.
