A Fast Feature Point Matching Algorithm Based on IMU Sensor

TL;DR

This paper introduces a fast feature point matching algorithm for SLAM that leverages IMU data to limit search areas, significantly reducing matching time and enhancing real-time performance on low-power systems.

Contribution

The proposed algorithm uses IMU data to optimize feature point matching, avoiding exhaustive searches and improving efficiency compared to traditional methods.

Findings

Reduced matching time in experiments

Improved real-time performance in SLAM

Effective use of IMU data for optimization

Abstract

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.